DETAILED ACTION
Notice to Applicant
The following is a NON-FINAL Office action upon examination of application number 18/506,783 filed on 11/10/2023, in response to Applicant’s Request for Continued Examination (RCE) filed on April 23, 2026. Claims 1-20 are pending in this application, and have been examined on the merits discussed below.
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Priority
Application 18/506,783 filed 11/10/2023 claims Priority from Provisional Application 63/424,292, filed 11/10/2022.
Response to Amendment
4. In the response filed April 23, 2026, Applicant amended claims 1, 14, and 20, and did not cancel any claims. No new claims were presented for examination.
5. Applicant's amendments to claims 1, 14, and 20 (with respect to the unabridged “API”) are hereby acknowledged. The amendments are sufficient to overcome the previously issued claim objection; accordingly, this objection has been removed.
6. Applicant did not amend the “computing a multi-modal transportation itinerary…” limitation in claim 1; accordingly, the previously issued claim objection (with respect to the lack of proper claim markings) has been maintained.
7. Applicant's amendments to claims 1, 14, and 20 are hereby acknowledged. The amendments are sufficient to overcome the previously issued claim rejection under 35 U.S.C. 112(b); accordingly, this rejection has been withdrawn. However, a new rejection under 35 U.S.C. 112(b) has been raised in view of the claim amendments.
8. Applicant's amendments to claims 1, 14, and 20 are hereby acknowledged. The amendments are not sufficient to overcome the previously issued claim rejection under 35 U.S.C. 101; accordingly, this rejection has been maintained.
Response to Arguments
9. Applicant's arguments filed April 23, 2026, have been fully considered.
10. Applicant submits “First, the Office Action improperly invokes the "managing personal behavior or relationships or interactions between people" exception category. The Office Action alleges that the claims "recite steps for coordinating multi-leg transportation and matching drivers/vehicles to requests for transporting a rider to a requested destination, which encompasses activity for managing personal behavior or relationships or interactions (e.g., following rules or instructions)." Id. This allegation is a stark deviation from the provided guidance around the "managing personal behavior or relationships or interactions between people" exception category. According to the MPEP, "certain methods of organizing human activity" include "[1] fundamental economic principles or practices, [2] commercial or legal interactions, and [3] managing personal behavior, relationships or interactions between people." See MPEP § 2106.04(a). "The term "certain" qualifies the "certain methods of organizing human activity' grouping as a reminder" that "not all methods of organizing human activity are abstract ideas" and "this grouping is limited to activity that falls within the enumerated sub-groupings of fundamental economic principles or practices, commercial or legal interactions, managing personal behavior, and relationships or interactions between people, and is not to be expanded beyond these enumerated sub-groupings except in rare circumstances." Id. According to the MPEP, "sub-grouping managing personal behavior or relationships or interactions between people' include social activities, teaching, and following rules or instructions." MPEP § 2106.04(a)(2)(II)(C). In § 2106, the MPEP gives the following examples of such interactions: tracking financial transactions to determine whether they exceed a pre-set spending limit (i.e., budgeting), filtering content, considering historical usage information while inputting data, a mental process that a neurologist should follow when testing a patient for nervous system malfunctions Applicant respectfully submits that the subject matter of the present claims is entirely dissimilar to these examples. The Office Action sets out no explanation of how the claimed technique could be classified as any of “social activities, teaching, and following rules or instructions.” instructions." Nor does the Office Action provide any indication of how the present claims have any similarities with the MPEP's examples. Thus, the Office Action fails to establish a prima facie case that any claim is patent ineligible.” [Applicant’s Remarks, 04/23/2026, pages 11-12]
The Examiner respectfully disagrees. In response, it is noted that claim 1 recites a method for managing multi-modal transportation services involving a user, transportation legs, quality measurements, and adjustment actions based those measurements. When considered as whole, the claim recites limitations related to coordinating and managing interaction between people (i.e., users, drivers) according to a set of rules and decision logic governing transportation services. Specifically, the claim recites the steps of accessing data indicative of a request for a transportation service, computing a multi-modal transportation itinerary for the user based on the request, generating a register of computing devices associated with the multi-modal transportation itinerary for the user, determining a state of the user relative to the multi-modal transportation itinerary, computing a quality measurement of the multi-modal transportation service based on the state of the use, determining, while the multi-modal transportation itinerary is in progress, an adjustment action associated with the multi-modal transportation itinerary for the user based on the quality measurement, adjusting the multi-modal transportation itinerary, and alerting a user of the adjusted multi-modal transportation itinerary. These steps collectively describe managing a transportation service workflow, which involves organizing human activity by coordinating transportation services for a user.
Moreover, it is noted that the claims recite limitations related to coordinating a multi-leg transportation service involving a rider and multiple service providers, including determining the rider’s state, evaluating service quality, and determining adjustment actions for subsequent transportation legs. These steps set forth decision criteria that governs how the rider and providers interact throughout the service. As such, the claims reasonably encompass managing interactions between people, including following rules or instructions for coordinating these interactions. For the reasons above, this argument is found unpersuasive.
12. Applicant submits “Although claim 1 includes "accessing data indicative of a request for a transportation service, wherein the request is indicative of a user of the transportation service," the claim does not end there. The claim as a whole does NOT relate to mere methods of organizing human behavior or managing personal behavior or relationships or interactions between people. In contrast, the subject matter of claim 1 is further directed to analyzing an end-to-end trip experience and make real-time adjustments to the rider's trip based on the rider's calculated experience, across an ecosystem of distributed computing devices. See, e.g., Specification at Para. [0168].” [Applicant’s Remarks, 04/23/2026, page 13]
The Examiner respectfully disagrees. In response to Applicant’s argument it is noted that the assertion that the “claim as a whole does not relate to mere methods of organizing human behavior” is not persuasive because the recited limitations are fundamentally rooted in coordinating and evaluating a transportation service between a rider and service providers. The claim limitations, as claimed, still collectively amount to evaluating service related information and determining subsequent service instructions within a transportation coordination workflow. For the reasons above, this argument is found unpersuasive.
13. Applicant submits “Second, the Office Action improperly invokes the "mental processes" exception category. The Office Action alleges that the claims recite "steps that can be performed in the human mind (including observation, evaluation, judgment, opinion)." Office Action at 13. This allegation is a stark deviation from the provided guidance around the "mental processes" exception category.” [Applicant’s Remarks, 04/23/2026, page 14]
The Examiner respectfully disagrees. In response to Applicant’s argument it is noted that
claim 1 recites limitations related to collecting information, evaluating that information using rules, and determining actions based on the evaluation to manage transportation services. Specifically, the steps of related to receiving a transportation request, determining user’s state relative to an itinerary, computing a quality measurement, and determining and adjustment action reflect judgment based decision making that can be performed mentally with the aid of pen and paper. The amended limitations of generating a register, accessing data via APIs, and transmitting instructions over a network merely describe mechanisms for implementing these mental steps using a computer. The underlying concepts (i.e., assessing service quality and deciding how to adjust service legs) can be performed by a human using written records, schedules, and predefined rules, and therefore also falls under the “Mental Processes” abstract idea grouping.
In other words, the claim limitations involve assessing information and making determination based on that information, which are activities that fall within the mental processes grouping. Implementing these operations using generic computing component does not remove them from this category. For the reasons detailed above, this argument is found unpersuasive.
14. Applicant submits “Like Example 38, independent claim 1 does not recite a mental process because the steps are not practically performed in the human mind.” [Applicant’s Remarks, 04/23/2026, page 15]
The Examiner respectfully disagrees. With respect to Applicant's comparison to Example 38, Examiner points out that the claimed invention in Example 38 addresses the inability of replicating the sound quality of an analog audio mixer in prior art methods by accounting for the slight variances in analog circuit values that are generated during the circuit’s manufacturing. By simulating these variances, a more authentic sound can be created that is preferential for the listener. As stated in Example 38, the claim recites “A method for providing a digital computer simulation of an analog audio mixer comprising: initializing a model of an analog circuit in the digital computer, said model including a location, initial value, and a manufacturing tolerance range for each of the circuit elements within the analog circuit; generating a normally distributed first random value for each circuit element, using a pseudo random number generator, based on a respective initial value and manufacturing tolerance range; and simulating a first digital representation of the analog circuit based on the first random value and the location of each circuit element within the analog circuit.” The Examiner notes that the claims in Example 38 do not recite any of the judicial exceptions enumerated in MPEP 2106. “For instance, the claim does not recite a mathematical relationship, formula, or calculation. While some of the limitations may be based on mathematical concepts, the mathematical concepts are not recited in the claims. With respect to mental processes, the claim does not recite a mental process because the steps are not practically performed in the human mind. Finally, the claim does not recite a certain method of organizing human activity such as a fundamental economic concept or commercial and legal interactions. The claim is eligible because it does not recite a judicial exception.” The claims at issue are far different from the claims in Example 38. The claims of the present case involve a method for coordination of multi-leg transportation. More specifically, claim 1 recites limitations related to determining a user’s state in relation to a transportation itinerary, evaluating a service quality measurement, and determining an adjustment action based on that evaluation. These steps involve collecting information, assessing conditions, and reaching determinations based on that information, which are activities that can be practically performed using human observation and reasoning. Unlike Example 38, the claim does not include comparable technical constraints that would take the recited limitations outside the mental processes abstract idea grouping. For the reasons detailed above, this argument is found unpersuasive.
15. Applicant submits “The human mind cannot practically generate "a register of computing devices associated with the multi-modal transportation itinerary for the user, the register of computing devices being indicative of a plurality of computing devices of a distributed computing ecosystem," or access "via one or more messages structured according to one or more Application Programming Interfaces (APIs), data from one or more of the computing devices included in the register." Nor is the human mind equipped to determine an "adjustment action [that] is configured to counteract a negative quality measurement subtracted from a predicted overall service score or emphasize a positive quality measurement added to the predicted overall service score, wherein a negative quality measurement is a weighted value of a negative user experience and a positive quality measurement is a weighted value of a positive user experience," let alone to transmit "over a network to at least one computing device of the register, an instruction to initiate the adjustment action or alert" or alert "a user device, via one or more messages structured according to the one or more APIs, of the adjusted multi-modal transportation itinerary”.” [Applicant’s Remarks, 04/23/2026, page 16]
The Examiner respectfully disagrees. In response to Applicant’s argument, it is noted that generating “a register of computing devices,” evaluating user experience weights, and determining adjustment actions based on a calculated service score are all rooted in organizing information, making comparative assessments, and arriving at determinations based on defined criteria. These are types of cognitive operations that fall within the mental processes abstract idea grouping when the underlying logic is considered, even if the claims additionally recites implementing those determinations using generic computing components. The recitation of distributed computing ecosystem, Application Programming Interfaces, and network transmission describes the environment in which these determinations occur, but does not alter the character of the claimed limitations. For the reasons detailed above, this argument is found unpersuasive.
16. Applicant submits “Applicant asserts that the claim recites a combination of elements such that the claim as a whole integrates the alleged abstract idea into a practical application.” [Applicant’s Remarks, 04/23/2026, page 16]
In response to Applicant’s argument “that the claim recites a combination of elements such that the claim as a whole integrates the alleged abstract idea into a practical application,” the Examiner respectfully disagrees. Under Step 2A Prong Two of the eligibility inquiry, any additional elements are evaluated individually and in combination to determine whether they integrate the judicial exception into a practical application, with consideration of the following exemplary considerations that may be indicative of a practical application: an additional element that reflects an improvement to the functioning of a computer or to any other technology or technical field, applying the exception with a particular machine, applying the judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, effecting a transformation of a particular article to a different state or thing, and applying or using the judicial exception some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment.
In this instance, the additional elements recited in exemplary claim 1 are: computing devices, the register of computing devices being indicative of a plurality of computing devices of a distributed computing ecosystem, via one or more messages structured according to one or more Application Programming Interfaces (APIs), one or more of the computing devices, a network, at least one computing device of the register, and a user device. These elements have been considered individually and in combination, however these computing elements amount to using a generic computer programmed with computer-executable instructions/software to perform the abstract idea, similar to adding the words “apply it” (or an equivalent), which merely serves to link the use of the judicial exception to a particular technological environment, which is not sufficient to amount to a practical application, as noted in the 2019 PEG. See also MPEP 2106.05(f) and 2106.05(h). Furthermore, these additional elements fail to provide an improvement to the functioning of a computer or to any other technology or technical field, fail to apply the exception with a particular machine, fail to apply the judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, fail to effect a transformation of a particular article to a different state or thing, and fail to apply/use the abstract idea in a meaningful way beyond generally linking the use of the judicial exception to a particular technological environment. Instead, the requestor device amounts to using generic computing devices as tools to implement the abstract idea, which does not amount to a technological improvement or otherwise indicate a practical application. See MPEP 2106.05(f).
The Examiner emphasizes that nowhere in Applicant’s Specification is there any discussion or suggestion that the problem or solution is a technical one, nor is there even a hint of any contemplated improvement to technology. It is not clear how the claimed limitations provide an actual improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment evident in the claims. The Applicant’s claims do not adequately explain how the additional elements of the claim integrate to add any meaningful limits on the abstract idea. At the most, the claimed invention seems to provide improvement beneficial to the end users. While the methods may improve the business process of determining an adjustment action associated with the transportation itinerary, there is no improvement to another technology or technical field. The focus of the claims of the instant application is not on such an improvement in computers as tools, but on certain independently abstract ideas that use computers as tools. Even reviewing the Applicant’s Specification (which describes the hardware and software), it is not made clear how the hardware and software result in an improvement to the technology or hardware itself, etc. The claimed invention does not provide an improvement to another technology/technical field or the functioning of the computer itself. Applicant's invention is directed towards providing business solutions to business problems rather than providing technical solutions to technical problems; thus, the claimed invention does not provide an improvement to another technology/technical field or the functioning of the computer itself. The Examiner further points out there is no actual improvement to another technology or technical field, no improvement to the functioning of the computer itself, and no meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment evident in the claims.
Lastly, it is noted that Applicant’s claims are devoid of any discernible change, transformation, or improvement to a computer (software or hardware) or any existing technology. Applicant has not shown that any specific technological improvement is achieved within the scope of the claims. It bears emphasis that no computing device, Application Programming Interfaces, user device, or technological elements are modified or improved upon in any discernible manner. Instead, the result produced by the claims is simply information related to the adjusted multi-modal transportation itinerary, which is not a technical result or improvement thereof. For the reasons above, this argument is found unpersuasive.
17. Applicant submits “Like Example 48, the subject claims recite specific features that reflect a technical improvement described in the disclosure. For example, specific features of amended claim 1 address technical problems associated with "leverage[ing] a specific computing ecosystem and a plurality of discrete user states to improve the computing efficiency, accuracy, and personalization for the real-time monitoring and adjustment of transportation services." Specification at Para. [0045]. The method of claim 1 "correlate[es] the real-time quality measurements with the discrete user states, actions for improving the transportation service can be tailored to a specific location or activity associated with a negative quality measurement." Id. at Para. [0046]. Furthermore, the claimed technology improves the "computing system that can accumulate and distribute newly available information such as, for example, real-time quality measurements tied to discrete user states to provide a practical application that improves the utilization of computing systems for the facilitation of transportation services." Id. This allows for constant monitoring of a user's itinerary, itinerary adjustments, and updates to the user's device to provide updates and courses of action.” [Applicant’s Remarks, 04/23/2026, page 18]
The Examiner respectfully disagrees. With respect to Applicant's comparison to Example 48, Examiner points out that that the claim recites limitations related to receiving transportation data, determining user state, evaluating a quality measurement, and determining an adjustment actin based on that evaluation. These steps describe information collection, analysis, and decision making applied in a transportation context, implemented using generic computing components. The use of a distributed computing environment does not by itself establish a technical improvement to the functioning of the computer or network.
The cited passages of the Specification describe benefit such as improved efficiency, accuracy, and personalization in managing transportation services. However, these are improvements to the service or information processing outcome, not the underlying computer or network technology itself. Unlike Example 48, the claim does not provide an improvement in computer functionality or operation. For the reasons detailed above, this argument is found unpersuasive.
18. Applicant submits “that claim 1 is not rendered obvious by the cited references because the cited references fail to teach or suggest the features of claim 1 including, for example, the above highlighted features of claim 1. Accordingly, Applicant requests the withdrawal of the rejection of claim 1 under 35 U.S.C. § 103.” [Applicant’s Remarks, 04/23/2026, page 21]
In response to Applicant’s argument, it is noted that this argument is a mere allegation of patentability by the Applicant with no supporting rationale or explanation. Merely stating that the claims do not teach a feature does not offer any insight as to why the specific sections of the prior art relied upon by the Examiner fail to disclose the claimed features. Applicant's arguments amount to a general allegation that the claims define a patentable invention without specifically pointing out how the language of the claims patentably distinguishes them from the references. Moreover, the Examiner notes that the “above highlighted features of claim 1” (i.e., wherein the adjustment action is configured to counteract a negative quality measurement subtracted from a predicted overall service score or emphasize a positive quality measurement added to the predicted overall service score, wherein a negative quality measurement is a weighted value of a negative user experience and a positive quality measurement is a weighted value of a positive user experience; wherein initiating the adjustment action comprises adjusting the multi-modal transportation itinerary based on the predicted overall service score; and alerting a user device, via one or more messages structured according to the one or more APIs, of the adjusted multi-modal transportation itinerary) have been addressed in the updated rejection below. Applicant’s argument has been considered, but it pertains to amendments to independent claim 1 that are believed to be addressed via the new ground of rejection under §103 set forth in the instant Office action, which incorporates new citations and a new reference to address the amended limitations in claim 1 and supports a conclusion of obviousness of the amended claims. Accordingly, the amendment and supporting arguments are believed to be fully addressed via the updated ground of rejection set forth under §103 below.
19. Applicant's remaining arguments either logically depend from the above-rejected arguments, in which case they too are unpersuasive for the reasons set forth above, or they are directed to features which have been newly added via amendment. Therefore, this is now the Examiner's first opportunity to consider these limitations and as such any arguments regarding these limitations would be inappropriate since they have not yet been examined. A full rejection of these limitations will be presented later in this Office Action.
Claim Objections
20. Claim 1 is objected to because of the following informalities: markings to show changes to the claim.
Claim 1 was previously amended (Claims dated 11/24/2025) to recite “computing a multi-modal transportation itinerary for the user based on the request, wherein the multi-modal transportation itinerary comprises a plurality of transportation legs for providing a multi-modal transportation service.” However, original claim 1 recited “computing a multi-modal transportation itinerary for the user based on the request, wherein the multi-modal transportation itinerary comprises a plurality of transportation legs for providing the multi-modal transportation service.” Claim 1 (Claims dated 11/24/2025) was presented without strike-through for deleted matter (i.e., the article “the” was deleted instead of being shown with strike-through), which is improper since changes in any amended claim must be shown by strike-through (for deleted matter). As per 37 CFR 1.121, all claims being currently amended must be presented with markings to indicate the changes that have been made relative to the immediate prior version. The changes in any amended claim must be shown by strike-through (for deleted matter) or underlining (for added matter) with 2 exceptions: (1) for deletion of five or fewer consecutive characters, double brackets may be used; (2) if strike-through cannot be easily perceived (e.g., deletion of number “4” or certain punctuation marks), double brackets must be used (e.g., [[4]]). As an alternative to using double brackets, however, extra portions of text may be included before and after text being deleted, all in strike-through, followed by including and underlining the extra text with the desired change. The “computing” limitation should be amended to show “wherein the multi-modal transportation itinerary comprises a plurality of transportation legs for providing [[the]] a multi-modal transportation service.” Appropriate correction is required. See 37 CFR 1.121. In the interest of compact prosecution, the Examiner has addressed the amended limitation.
Original claim 1 is reproduced below (as presented on 11/20/2023)
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Amended claim 1 is reproduced below (as presented on 11/24/2025)
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Claim 1 is reproduced below (as presented on 04/23/2026)
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Claim Rejections - 35 USC § 112
21. The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
22. Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
23. Claims 1/14/20 were amended to recite “wherein the adjustment action is configured to counteract a negative quality measurement subtracted from a predicted overall service score or emphasize a positive quality measurement added to the predicted overall service score.” This limitation renders the scope of the claim unclear. Specifically it is unclear whether the “subtracted from” and “added to” refer to specific arithmetic operations, weighting factors within a scoring model, or general directional effects on an evaluative metric. The claim does not set forth a mathematical relationship by which the quality measurements are combined or applied. The Specification describes that the overall service score is computed as an aggregation of weighted quality measurements based on user states, where weights may vary across users and are learned or adjusted over time (paragraphs 0154, 0194-0196, 0249-0251). However, the claim does not clearly align the “added” and “subtracted” language with this describes aggregation and weighting framework, resulting in ambiguity as to the metes and bound of the claimed scoring relationship. Therefore, the claims are rendered indefinite. For examination purposes, the limitation is interpreted as referring to a weighted aggregation in which positive quality measurements contribute to increasing an overall service score and negative quality measurements contribute to decreasing the overall service score. Appropriate correction is required.
24. Claims 2-13 depend from claim 1 and therefore inherit the §112(b) deficiencies of claim 1. Claims 15-19 depend from claim 14 and therefore inherit the §112(b) deficiencies of claim 14.
Claim Rejections - 35 USC § 101
25. 35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
26. Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The eligibility analysis in support of these findings is provided below, in accordance with MPEP 2106.
With respect to Step 1 of the eligibility inquiry (as explained in MPEP 2106), it is first noted that the method (claims 1-13), computer program product (claims 14-19), and system (claim 20) is directed to at least one potentially eligible category of subject matter (i.e., process, article of manufacture, and machine, respectively). Thus, Step 1 of the Subject Matter Eligibility test for claims 1-20 is satisfied.
With respect to Step 2A Prong One, it is next noted that the claims recite an abstract idea that falls into the “Certain Methods of Organizing Human Activity” abstract idea set forth in MPEP 2106 because the claims recite steps for coordinating multi-leg transportation and matching drivers/vehicles to requests for transporting a rider to a requested destination, which encompasses activity for managing personal behavior or relationships or interactions (e.g., following rules or instructions), and steps that can be performed in the human mind (including observation, evaluation, judgment, opinion), and therefore fall under the “Mental Processes” abstract idea grouping. With respect to independent claim 1, the limitations reciting the abstract idea are indicated in bold below: accessing data indicative of a request for a transportation service, wherein the request is indicative of a user for the transportation service; computing a multi-modal transportation itinerary for the user based on the request, wherein the multi-modal transportation itinerary comprises a plurality of transportation legs for providing a multi-modal transportation service; generating a register of computing devices associated with the multi-modal transportation itinerary for the user, the register of computing devices being indicative of a plurality of computing devices of a distributed computing ecosystem; accessing, via one or more messages structured according to one or more Application Programming Interfaces (APIs), data from one or more of the computing devices included in the register; determining, based on the data from the one or more computing devices included in the register, a state of the user relative to the multi-modal transportation itinerary, wherein the state is indicative of a progress of the multi-modal transportation service for the user, and wherein the state is associated with a transportation leg of the multi-modal transportation itinerary; computing a quality measurement of the multi-modal transportation service based on the state of the user; determining, while the multi-modal transportation itinerary is in progress, an adjustment action associated with the multi-modal transportation itinerary for the user based on the quality measurement, wherein the adjustment action comprises an adjustment associated with another transportation leg of the multi-modal transportation itinerary, the other transportation leg being subsequent to the transportation leg, and wherein the adjustment action is configured to counteract a negative quality measurement subtracted from a predicted overall service score or emphasize a positive quality measurement added to the predicted overall service score, wherein a negative quality measurement is a weighted value of a negative user experience and a positive quality measurement is a weighted value of a positive user experience; transmitting, over a network to at least one computing device of the register, an instruction to initiate the adjustment action associated with the multi-modal transportation itinerary for the user, wherein initiating the adjustment action comprises adjusting the multi-modal transportation itinerary based on the predicted overall service score; and alerting a user device, via one or more messages structured according to the one or more APIs, of the adjusted multi-modal transportation itinerary. These steps are organizing human activity by managing interactions between people by following rules, or instructions, and may also be accomplished mentally such as via human observation and perhaps with the aid of pen and paper.
Therefore, because the limitations above set forth activities falling within the “Certain methods of organizing human activity” and “Mental Processes” abstract idea grouping described in MPEP 2106, the additional elements recited in the claims are further evaluated, individually and in combination, under Step 2A Prong Two and Step 2B below. Independent claims 14 and 20 recite similar limitations as those discussed above and are therefore found to recite the same or substantially the same abstract idea as claim 1.
With respect to Step 2A Prong Two, the judicial exception is not integrated into a practical application. With respect to the independent claims, the additional elements are: computing devices, the register of computing devices being indicative of a plurality of computing devices of a distributed computing ecosystem, via one or more messages structured according to one or more Application Programming Interfaces (APIs), one or more of the computing devices, a network, at least one computing device of the register, and a user device (claim 1), instructions that are executable by one or more processors, computing devices, the register of computing devices being indicative of a plurality of computing devices of a distributed computing ecosystem, via one or more messages structured according to one or more Application Programming Interfaces (APIs), one or more of the computing devices included, a network, at least one computing device of the register, and a user device (claim 14), one or more processors, one or more tangible, non-transitory, computer readable media that store instructions that are executable by the one or more processors, the computing system, computing devices, the register of computing devices being indicative of a plurality of computing devices of a distributed computing ecosystem, via one or more messages structured according to one or more Application Programming Interfaces (APIs), one or more of the computing devices, a network, at least one computing device of the register, and a user device (claim 20). These additional elements have been evaluated, but fail to integrate the abstract idea into a practical application because they amount to using generic computing elements or computer-executable instructions (software) to perform the abstract idea, similar to adding the words “apply it” (or an equivalent), and merely serve to link the use of the judicial exception to a particular technological environment. See MPEP 2106.05(f) and 2106.05(h). Even if the steps for accessing and transmitting are not deemed part of the abstract idea, these steps are at most directed to insignificant extra-solution activity, which is not sufficient to amount to a practical application. See MPEP 2106.05(g). In addition, these limitations fail to provide an improvement to the functioning of a computer or to any other technology or technical field, fail to apply the exception with a particular machine, fail to apply the judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, fail to effect a transformation of a particular article to a different state or thing, and fail to apply/use the abstract idea in a meaningful way beyond generally linking the use of the judicial exception to a particular technological environment.
Accordingly, because the Step 2A Prong One and Prong Two analysis resulted in the conclusion that the claims are directed to an abstract idea, additional analysis under Step 2B of the eligibility inquiry must be conducted in order to determine whether any claim element or combination of elements amount to significantly more than the judicial exception.
With respect to Step 2B of the eligibility inquiry, it has been determined that the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. With respect to the independent claims, the additional elements are: computing devices, the register of computing devices being indicative of a plurality of computing devices of a distributed computing ecosystem, via one or more messages structured according to one or more Application Programming Interfaces (APIs), one or more of the computing devices, a network, at least one computing device of the register, and a user device (claim 1), instructions that are executable by one or more processors, computing devices, the register of computing devices being indicative of a plurality of computing devices of a distributed computing ecosystem, via one or more messages structured according to one or more Application Programming Interfaces (APIs), one or more of the computing devices included, a network, at least one computing device of the register, and a user device (claim 14), one or more processors, one or more tangible, non-transitory, computer readable media that store instructions that are executable by the one or more processors, the computing system, computing devices, the register of computing devices being indicative of a plurality of computing devices of a distributed computing ecosystem, via one or more messages structured according to one or more Application Programming Interfaces (APIs), one or more of the computing devices, a network, at least one computing device of the register, and a user device (claim 20). These elements have been considered individually and in combination, but fail to add significantly more to the claims because they amount to using generic computing elements or instructions (software) to perform the abstract idea, similar to adding the words “apply it” (or an equivalent), and merely serve to link the use of the judicial exception to a particular technological environment and does not amount to significantly more than the abstract idea itself. Notably, Applicant’s Specification suggests that virtually any type of computing device under the sun can be used to implement the claimed invention (Specification at paragraph [0255]). Accordingly, the generic computer involvement in performing the claim steps merely serves to generally link the use of the judicial exception to a particular technological environment, which does not add significantly more to the claim. See, e.g., Alice Corp., 134 S. Ct. 2347, 110 USPQ2d 1976.). Next, the steps for accessing and transmitting are considered insignificant extra-solution activity, which has been recognized as well-understood, routine, and conventional, and thus insufficient to add significantly more to the abstract idea. See MPEP 2106.05(d).
In addition, when taken as an ordered combination, the ordered combination adds nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements integrate the abstract idea into a practical application. Their collective functions merely provide generic computer implementation. Therefore, when viewed as a whole, these additional claim elements do not provide meaningful limitations to transform the abstract idea into a practical application of the abstract idea or that, as an ordered combination, amount to significantly more than the abstract idea itself.
Dependent claims 2-13 and 15-19 recite the same abstract idea as recited in the independent claims, and when evaluated under Step 2A Prong One are found to merely recite details that serve to narrow the same abstract idea recited in the independent claims accompanied by the same generic computing elements or software as those addressed above in the discussion of the independent claims, which is not sufficient to amount to a practical application or add significantly more, or other additional elements that fail to amount to a practical application or add significantly more, as noted above. In particular, dependent claims 2-13 and 15-19 recite “wherein the other transportation leg comprises a ground transportation service for the user, and wherein the adjustment action comprises at least one of: (i) initiating an adjustment to the ground transportation for the user; or (ii) initiating an increase in a priority associated with the user for the ground transportation,” “wherein adjusting the ground transportation for the user comprises at least one of: (i) assigning a different ground vehicle to the user; (ii) changing a service level associated with the ground transportation for the user; or (iii) changing a service type associated with the ground transportation,” “wherein increasing the priority associated with the user for the ground transportation comprises adjusting a data structure for assigning a ground vehicle to the user to increase the priority with which the ground vehicle is assigned to the user,” “wherein the other transportation leg comprises an aerial transportation service for the user, and wherein the adjustment action comprises at least one of: (i) initiating an adjustment of a seat for the user on an aircraft to be used for the aerial transportation service; or (ii) initiating an assignment of the user to a different aircraft for the aerial transportation service,” “wherein computing the quality measurement of the multi-modal transportation service based on the state of the user comprises: accessing data associated with the multi-modal transportation service, wherein the data associated with the multi-modal transportation services comprises at least one of timing data, movement data, data associated with another user, or event data received from at least one of a plurality of distributed computing devices associated with the multi-modal transportation service; and computing the quality measurement of the multi-modal transportation service based on the state of the user and the data associated with the multi-modal transportation service,” “wherein computing the quality measurement of the multi-modal transportation service based on the state of the user and the data associated with the multi-modal transportation service comprises: accessing a time threshold associated with the state of the user, wherein the time threshold is based on historical transportation data for the user state; computing a state waiting time for the user based on the data associated with the multi-modal transportation service, the state waiting time descriptive of a period of time that the user remains in the user state; and computing the quality measurement based on a comparison of the time threshold and the state waiting time,” “wherein the user is associated with one or more user characteristics, and wherein the time threshold associated with the user state is based the one or more user characteristics,” “wherein the time threshold associated with the user state is based on a geographic region associated with the multi-modal transportation service,” “wherein determining the adjustment action associated with the multi-modal transportation itinerary for the user based on the quality measurement comprises: computing the predicted overall service score for the multi-modal transportation service based on the quality measurement, wherein the predicted overall service score is indicative of a predicted quality of the multi-modal transportation service across a plurality of states of the multi-modal transportation service; and determining the adjustment action based on the predicted overall service score, wherein the adjustment action is configured to impact a final overall service score,” “wherein computing the predicted overall service score for the multi-modal transportation service comprises: determining a weighted quality measurement based on the user state; and computing the predicted overall service score based on the weighted quality measurement,” “wherein computing the predicted overall service score for the multi-modal transportation service comprises: accessing one or more other quality measurements of the multi-modal transportation service for one or more other states of the user relative to the multi-modal transportation itinerary; and computing the predicted overall service score based on an aggregation of the quality measurement and the one or more other quality measurements of the multi-modal transportation service,” “wherein the state is one of a plurality of predefined user states, the plurality of predefined user states comprising a transit state, a transitional state, a boarding state, a ready state, and an arrival state,” “wherein the adjustment action comprises a modification,” “provide one or more user notifications, and wherein initiating the adjustment action comprises: accessing alternative transportation data associated with an alternative transportation service; computing a user notification descriptive of a comparison between the alternative transportation service and the multi-modal transportation service; and transmitting data indicative of the user notification during the multi-modal transportation service,” “wherein the adjustment action comprises notifying an operator at an aerial facility to assist the user in transitioning between a ground transportation service to an aerial transportation service, and wherein transmitting the instruction to initiate the adjustment action comprises transmitting data indicative of a notification to assist the user while at the aerial facility,” “wherein the user state is one of a plurality of predefined user states, wherein each respective state is associated with a corresponding weight for determining a weight quality measurement associated with the respective state,” “wherein the operations further comprise: receiving feedback data associated with the transportation service; and modifying the corresponding weight of at least one respective state based on the feedback data”, however these limitations cover activity for managing personal behavior or relationships or interactions (e.g., following rules or instructions), which is part of the same abstract idea as addressed in the independent claims that falls within the “Certain Methods of Organizing Human Activity” abstract idea grouping and also recite steps that may also be accomplished mentally such as via human observation and perhaps with the aid of pen and paper. Dependent claims 15-17 recite additional elements of: a user device, a software application, at least one user interface of the software application, the network, and a user device associated with the operator. However, when evaluated under Step 2A Prong Two and Step 2B, these additional elements do not amount to a practical application or significantly more since they merely require generic computing devices (or computer-implemented instructions/code) which as noted in the discussion of the independent claims above is not enough to render the claims as eligible.
The ordered combination of elements in the dependent claims (including the limitations inherited from the parent claim(s)) add nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide generic computer implementation. Accordingly, the subject matter encompassed by the dependent claims fails to amount to a practical application or significantly more than the abstract idea itself.
For more information, see MPEP 2106.
Claim Rejections - 35 USC § 103
27. In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
28. The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
29. The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
30. This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
31. Claims 1-3, 5-6, 10, 12, 14-16, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Courtney et al., Pub. No.: US 2022/0147884 A1, [hereinafter Courtney] in view of Gulati, Pub. No.: US 2021/0407031 A1, [hereinafter Gulati], in further view of Kline et al., Pub. No.: US 2021/0025721 A1, [hereinafter Kline].
As per claim 1, Courtney teaches a computer-implemented method (paragraph 0020: “Aspects of the present disclosure are directed to improved systems and methods for multi-modal transportation services.”; paragraph 0006) comprising:
accessing data indicative of a request for a transportation service, wherein the request is indicative of a user for the transportation service (paragraph 0020, discussing systems and methods for multi-modal transportation services…A service entity computing system associated with the service entity can obtain data indicative of a service request from one or more riders and generate one or more multi-modal transportation itineraries (e.g., rider itinerary, ground itinerary, flight itinerary, subterranean itinerary, nautical itinerary, etc.) to facilitate transporting the rider from the origin location to the destination location…; paragraphs 0025, 0045);
computing a multi-modal transportation itinerary for the user based on the request, wherein the multi-modal transportation itinerary comprises a plurality of transportation legs for providing a multi-modal transportation service (paragraph 0020, discussing that a service entity computing system associated with the service entity can obtain data indicative of a service request from one or more riders and generate one or more multi-modal transportation itineraries (e.g., rider itinerary, ground itinerary, flight itinerary, subterranean itinerary, nautical itinerary, etc.) to facilitate transporting the rider from the origin location to the destination location…; paragraph 0027, discussing that the service entity computing system can perform one or more algorithms to generate the end-to-end multi-modal itinerary for a rider…; paragraph 0080, discussing that in response to the rider's request, the service entity computing system can perform one or more algorithms to generate a multi-modal transportation itinerary for the rider. As an example, in some implementations, the service entity computing system can sequentially analyze and identify potential transportation legs for each different available transportation modality; paragraphs 0029, 0078);
generating a register of computing devices associated with the multi-modal transportation itinerary for the user, the register of computing devices being indicative of a plurality of computing devices of a distributed computing ecosystem (paragraph 0069, discussing that the service entity computing system can be communicatively connected over a network to the vehicle provider computing system(s), one or more rider computing devices, one or more service provider computing devices for a first ground transportation leg, one or more service provider computing devices for a second ground transportation leg, one or more service provider computing devices for an Nth ground transportation leg, and/or one or more infrastructure and operations computing devices. For example, the vehicle provider computing system(s) can include one or more communication interfaces communicatively connected to the service entity computing system and the service entity computing system can include one or more communication interfaces communicatively connected to the vehicle provider computing system(s); paragraph 0070, discussing that each of the computing devices can include any type of computing device such as a smartphone, tablet, hand-held computing device, wearable computing device, embedded computing device, navigational computing device, vehicle computing device, etc.; paragraph 0083, discussing that transportation nodes can include charging equipment, re-fueling equipment, and/or other infrastructure for enabling aerial operation. The infrastructure and operations computing devices can be any form of computing device used by and/or at the infrastructure…; paragraph 0090);
accessing, via one or more messages structured according to one or more Application Programming Interfaces (APIs), data from one or more of the computing devices included in the register (paragraph 0026, discussing that the service entity computing system can provide access to one or more services of the service entity to systems (e.g., third-party vehicle computing systems, third-party air traffic control systems, etc.) associated with third-party vehicle providers. As described herein, the service entity computing system can generate end-to-end itineraries for third party vehicles. In some implementations, this can be accomplished by utilizing information obtained via the third party vehicle provider (e.g., its associated computing system); paragraph 0090, discussing that the world state system can generate, collect, and/or maintain data descriptive of planned itineraries; pre-determined transportation plans and assignments; current requests; current ground transportation service providers; current aerial transport facility operational statuses ; current aerial vehicle statuses; current pilot statuses; current flight states and trajectories; current airspace information; current weather conditions; current communication system behavior/protocols; and/or the like. For instance, the world state system can be configured to obtain world state data through communication (e.g., via an API platform) with one or more vehicles (e.g., via service provider device(s)), vehicle providers (e.g., vehicle provider computing system(s)), and/or any other transportation entity associated with the service entity computing system; paragraph 0092, discussing that each respective matching system can communicate with the corresponding service provider computing devices via one or more APIs or connections.);
determining, based on the data from the one or more computing devices included in the register, a state of the user relative to the multi-modal transportation itinerary, wherein the state is indicative of a progress of the multi-modal transportation service for the user, and wherein the state is associated with a transportation leg of the multi-modal transportation itinerary (paragraph 0078, discussing that the service entity computing system can respond to the rider's request by determining whether it is better to fulfill the rider's request using a single transportation modality or using multiple transportation modalities…The service entity computing system can evaluate the rider's current location, origin location, and/or destination location to determine which modalities of transportation are usable at such location; paragraph 0079, discussing that the service entity computing system can continually re-evaluate various itineraries before and even during completion of a selected itinerary. If an improved itinerary becomes available the service entity computing system can suggest the improved itinerary for selection by the rider. In some implementations, if the rider selects, via the rider computing device(s), the improved itinerary during completion of an existing itinerary, the service entity computing system can facilitate switching to the updated itinerary, including, for example, re-routing a service provider that is currently transporting the rider to an alternative, updated destination; paragraph 0093, discussing that the monitoring and mitigation system can perform monitoring of rider itineraries and can perform mitigation when an itinerary is subject to significant delay (e.g., one of the legs fails to succeed). Thus, the monitoring and mitigation system can perform situation awareness, advisories, adjustments, and the like. The monitoring and mitigation system can trigger alerts and actions sent to the systems or devices. For example, entities such as riders, service providers, and/or operations personnel can be alerted when a certain transportation plan has been modified and can be provided with an updated plan/course of action. Thus, the monitoring and mitigation system can have additional control over the movement of aerial vehicles, ground vehicles, air traffic controllers, pilots, and rider; paragraph 0090);
computing a quality measurement of the multi-modal transportation service based on the state of the user (paragraph 0023, discussing that during the operational time period, the service entity computing system can determine a deviation from the number of aerial vehicles. In response, the service entity computing system can generate modified multi-modal transportation itineraries to compensate for the deviation and one or more deviation offset(s) to offset inefficiencies of the modified multi-modal transportation itineraries to the aerial vehicle provider; paragraph 0093, discussing that the monitoring and mitigation system can perform monitoring of rider itineraries and can perform mitigation when an itinerary is subject to significant delay (e.g., one of the legs fails to succeed). Thus, the monitoring and mitigation system can perform situation awareness, advisories, adjustments, and the like. The monitoring and mitigation system can trigger alerts and actions sent to the systems or devices. For example, entities such as riders, service providers, and/or operations personnel can be alerted when a certain transportation plan has been modified and can be provided with an updated plan/course of action. Thus, the monitoring and mitigation system can have additional control over the movement of aerial vehicles, ground vehicles, air traffic controllers, pilots, and riders; paragraphs 0034, 0036);
determining, while the multi-modal transportation itinerary is in progress, an adjustment action associated with the multi-modal transportation itinerary for the user based on the quality measurement, wherein the adjustment action comprises an adjustment associated with another transportation leg of the multi-modal transportation itinerary, the other transportation leg being subsequent to the transportation leg (paragraph 0047, discussing that in some cases, (e.g., during the provision of the multi-modal transportation itinerary(s)) the service entity computing system can determine a deviation associated with the flight data from at least one aerial vehicle provider. A deviation, for example, can be indicative of a lower number of aerial vehicles at one or more time(s) during the operational time period than provided by the flight data. In the event of a deviation, the service entity computing system (e.g., a monitoring and mitigation system) can mitigate the aerial vehicle provider's failure to achieve the number of aerial vehicles identified by the flight data by generating one or more modified multi-modal transportation itineraries based, at least in part, on the deviation and/or the multi-modal transportation itinerary(s). The modified multi-modal transportation itinerary(s), for example, can include one or more different flight itineraries than the original multi-modal transportation itinerary(s); paragraph 0048, discussing that the service entity computing system can generate the modified multi-modal transportation itinerary(s) by determining one or more multi-modal transportation itinerary(s) affected by the deviation. The affected multi-modal transportation itinerary(s), for example, can include multi-modal transportation itinerary(s) with an aerial transportation leg associated with an unavailable aerial vehicle. The service entity computing system can obtain one or more additional flight itineraries and/or any other flight data indicative of one or more available aerial vehicles and, based on this data, modify the aerial transportation leg of the affected multi-modal transportation itinerary(s). This can include replacing the aerial transportation leg with an available aerial vehicle, a vehicle of another modality (e.g., book another ground transportation vehicle, extend the first transportation leg to cover the second transportation leg, etc.), etc.; paragraph 0079, discussing that the service entity computing system can continually re-evaluate various itineraries (e.g., single- and/or multi-modal itineraries) before and even during completion of a selected itinerary. If an improved itinerary becomes available (e.g., which may include changing from a single-modal itinerary to a multi-modal itinerary if, for example, a seat on a flight becomes available) the service entity computing system can suggest the improved itinerary for selection by the rider. In some implementations, if the rider selects, via the rider computing device(s), the improved itinerary during completion of an existing itinerary, the service entity computing system can facilitate switching to the updated itinerary, including, for example, re-routing a service provider that is currently transporting the rider to an alternative, updated destination; paragraph 0093, discussing that the monitoring and mitigation system can perform monitoring of rider itineraries and can perform mitigation when an itinerary is subject to significant delay. Thus, the monitoring and mitigation system can perform situation awareness, advisories, adjustments, and the like. The monitoring and mitigation system can trigger alerts and actions sent to the systems or devices. For example, entities such as riders, service providers, and/or operations personnel can be alerted when a certain transportation plan has been modified and can be provided with an updated plan/course of action. Thus, the monitoring and mitigation system can have additional control over the movement of aerial vehicles, ground vehicles, air traffic controllers, pilots, and riders; paragraph 0049);
transmitting, over a network to at least one computing device of the register, an instruction to initiate the adjustment action associated with the multi-modal transportation itinerary for the user (paragraph 0048, discussing that the service entity computing system can generate the modified multi-modal transportation itinerary(s) by determining one or more multi-modal transportation itinerary(s) affected by the deviation. The affected multi-modal transportation itinerary(s), for example, can include multi-modal transportation itinerary(s) with an aerial transportation leg associated with an unavailable aerial vehicle. The service entity computing system can obtain one or more additional flight itineraries and/or any other flight data indicative of one or more available aerial vehicles and, based on this data, modify the aerial transportation leg of the affected multi-modal transportation itinerary(s). This can include replacing the aerial transportation leg with an available aerial vehicle, a vehicle of another modality (e.g., book another ground transportation vehicle, extend the first transportation leg to cover the second transportation leg, etc.), etc.; paragraph 0079, discussing that the service entity computing system can continually re-evaluate various itineraries before and even during completion of a selected itinerary. If an improved itinerary becomes available the service entity computing system can suggest the improved itinerary for selection by the rider. In some implementations, if the rider selects, via the rider computing device(s), the improved itinerary during completion of an existing itinerary, the service entity computing system can facilitate switching to the updated itinerary, including, for example, re-routing a service provider that is currently transporting the rider to an alternative, updated destination; paragraph 0093, discussing that the monitoring and mitigation system can perform monitoring of rider itineraries and can perform mitigation when an itinerary is subject to significant delay (e.g., one of the legs fails to succeed). Thus, the monitoring and mitigation system can perform situation awareness, advisories, adjustments, and the like. The monitoring and mitigation system can trigger alerts and actions sent to the systems or devices. For example, entities such as riders, service providers, and/or operations personnel can be alerted when a certain transportation plan has been modified and can be provided with an updated plan/course of action. Thus, the monitoring and mitigation system can have additional control over the movement of aerial vehicles, ground vehicles, air traffic controllers, pilots, and riders),
wherein initiating the adjustment action comprises adjusting the multi-modal transportation itinerary (paragraph 0048, discussing that the service entity computing system can generate the modified multi-modal transportation itinerary(s) by determining one or more multi-modal transportation itinerary(s) affected by the deviation. The affected multi-modal transportation itinerary(s), for example, can include multi-modal transportation itinerary(s) with an aerial transportation leg associated with an unavailable aerial vehicle. The service entity computing system can obtain one or more additional flight itineraries and/or any other flight data indicative of one or more available aerial vehicles and, based on this data, modify the aerial transportation leg of the affected multi-modal transportation itinerary(s). This can include replacing the aerial transportation leg with an available aerial vehicle, a vehicle of another modality (e.g., book another ground transportation vehicle, extend the first transportation leg to cover the second transportation leg, etc.), etc.; paragraph 0079, discussing that the service entity computing system can continually re-evaluate various itineraries before and even during completion of a selected itinerary. If an improved itinerary becomes available the service entity computing system can suggest the improved itinerary for selection by the rider. In some implementations, if the rider selects, via the rider computing device(s), the improved itinerary during completion of an existing itinerary, the service entity computing system can facilitate switching to the updated itinerary, including, for example, re-routing a service provider that is currently transporting the rider to an alternative, updated destination; paragraph 0093, discussing that the monitoring and mitigation system can perform monitoring of rider itineraries and can perform mitigation when an itinerary is subject to significant delay (e.g., one of the legs fails to succeed). Thus, the monitoring and mitigation system can perform situation awareness, advisories, adjustments, and the like. The monitoring and mitigation system can trigger alerts and actions sent to the systems or devices. For example, entities such as riders, service providers, and/or operations personnel can be alerted when a certain transportation plan has been modified and can be provided with an updated plan/course of action. Thus, the monitoring and mitigation system can have additional control over the movement of aerial vehicles, ground vehicles, air traffic controllers, pilots, and ride); and
alerting a user device, via one or more messages structured according to the one or more APIs, of the adjusted multi-modal transportation itinerary (paragraph 0093, discussing that the monitoring and mitigation system can perform monitoring of rider itineraries and can perform mitigation when an itinerary is subject to significant delay (e.g., one of the legs fails to succeed). Thus, the monitoring and mitigation system can perform situation awareness, advisories, adjustments, and the like. The monitoring and mitigation system can trigger alerts and actions sent to the systems or devices. For example, entities such as riders, service providers, and/or operations personnel can be alerted when a certain transportation plan has been modified and can be provided with an updated plan/course of action. Thus, the monitoring and mitigation system can have additional control over the movement of aerial vehicles, ground vehicles, air traffic controllers, pilots, and riders; paragraph 0079).
Courtney does not explicitly teach wherein the adjustment action is configured to counteract a negative quality measurement subtracted from a predicted overall service score or emphasize a positive quality measurement added to the predicted overall service score, wherein a negative quality measurement is a weighted value of a negative user experience and a positive quality measurement is a weighted value of a positive user experience; and wherein initiating the adjustment action comprises adjusting the multi-modal transportation itinerary based on the predicted overall service score. Gulati in the analogous art of transportation planning systems teaches
wherein the adjustment action is configured to counteract a negative quality measurement subtracted from a predicted overall service score or emphasize a positive quality measurement added to the predicted overall service score, wherein a negative quality measurement is a weighted value of a negative user experience and a positive quality measurement is a weighted value of a positive user experience (paragraph 0023, discussing that the transit itinerary system intelligently selects which alternative public transit itineraries to surface to user interfaces at the client device. For example, the transit itinerary system can weight the public transit itineraries based on one or more factors. In addition, the transit itinerary system can generate public transit itinerary scores for each of the alternative public transit itineraries and provide the alternative public transit itineraries that meet one or more threshold criteria; paragraph 0052, discussing that client device digital signals can include user input, such as a user interacting with the client device to provide positive or negative input with respect to a public transit itinerary and/or a public transit vehicle. In some implementations, additional computing devices can provide digital signals corresponding to a client device…Further, client devices associated with other users can provide secondary digital signals with respect to a public transit vehicle; paragraph 0070, discussing that the transit itinerary system utilizes a public transit itinerary generator to generate the alternative public transit itineraries. Further, the transit itinerary system can weight each of the alternative public transit itineraries based on various factors, such as transfer costs. In some implementations, the transit itinerary system can score the public transit itinerary and the (weighted) alternative public transit itineraries to determine if some of the alternative public transit itineraries are preferable to the current public transit itinerary. In these implementations, the transit itinerary system can provide the top-ranked alternative public transit itineraries to the client device; paragraph 0081, discussing that the transit itinerary system can weight, score, and/or rank the public transit itineraries. For example, the transit itinerary system applies a transfer cost weight to a segment that requires the client device to transfer to a new public transit vehicle. As another example, the transit itinerary system can rank the public transit itineraries based on features, labels, or categories…; paragraph 0148, discussing that the public transit itinerary generator includes an act of weighting the alternative public transit itineraries. Further, the public transit itinerary generator includes an act of scoring the alternative public transit itineraries as well as an act of selecting one or more alternative public transit itineraries to provide based on the scores; paragraph 0158, discussing that the public transit itinerary generator includes the act of weighting the alternative public transit itineraries. For instance, the transit itinerary system can apply a positive and negative weight to one or more of the public transit segments within an alternative public transit itinerary. Additionally, or in the alternative, the transit itinerary system can apply a positive and negative weight to the alternative public transit itinerary based on characteristics of the alternative public transit itinerary; paragraph 0159, discussing that the transit itinerary system adds a negative transfer cost weight to segments that require the client device to move to a new public transit vehicle between segments of the public transit itinerary. To illustrate, the transit itinerary system determines that a segment of an alternative public transit itinerary requires a client device to transfer to a second public transit vehicle from a first different public transit vehicle. In response, the transit itinerary system can add a transfer cost weight to the segment and/or alternative public transit itinerary…; paragraph 0160, discussing that the transit itinerary system can increase the transfer cost or apply an additional weight (e.g., a vehicle downgrade cost or a transfer type cost) when the transfer requires moving from one type of public transit vehicle to another type of public transit vehicle (e.g., moving from a train to a bus, or vice-versa)…; paragraph 0168, discussing that the transit itinerary system can generate multiple scores for an alternative public transit itinerary. For example, the transit itinerary system generates an overall score...When generating a label- or category-specific score for an alternative public transit itinerary, the transit itinerary system can give more weight to a particular factor; paragraph 0170, discussing that the transit itinerary system utilizes a scoring algorithm that applies positive and negative adjustments (e.g., weights) to segments of an alternative public transit itinerary and/or the alternative public transit itinerary as a whole as part of determining a score for the alternative public transit itinerary; paragraph 0190, discussing that the transit itinerary system can utilize weighting and scoring to identify one or more alternative public transit itineraries that are better (e.g., have higher scores)); and
wherein initiating the adjustment action comprises adjusting the multi-modal transportation itinerary (paragraph 0025, discussing that the transit itinerary system can proactively update the public transit itinerary. For example, the transit itinerary system automatically detects changes to the public transit itinerary previously provided to the client device. To illustrate, the transit itinerary system can identify delays in public transit vehicles that would alter a public transit itinerary. In response, the transit itinerary system can determine updates to the public transit itinerary and provide those updates to the client device without requiring any action on the part of the user; paragraph 0027, discussing that the transit itinerary system can provide public transit itinerary updates as well as alternative public transit itineraries to the client device in response to requests received by the client device. For example, while traveling on a public transit vehicle, the transit itinerary system can identify a user interaction that indicates a request for alternative public transit itineraries. In response, the transit itinerary system can generate and provide alternative public transit itineraries that are based on the client device currently traveling on the public transit vehicle; paragraph 0037, discussing that the transit itinerary system can provide accurate information, even in response to changes or delays in public transit vehicles or segments. Thus, when a client device utilizes an alternate public transit vehicle, a public transit vehicle is delayed, or when the client device requests a change to the public transit itinerary, the transit itinerary system can dynamically update the remaining segments of the public transit itinerary and provide those updates to the client device; paragraph 0049, discussing that the transit itinerary system can update a public transit itinerary provided to a client device as the client device is traveling along a public transit segment of the public transit itinerary. Often, a public transit itinerary includes multiple public transit segments of multiple public transit routes and multiple public transit vehicles with transfers between the public transit vehicles; paragraph 0110, discussing that the transit itinerary system generates an alternative public transit itinerary that alters and/or updates the current public transit itinerary. For example, based on detecting changes to the public transit itinerary provided to the client device, the transit itinerary system can generate one or more alternative public transit itineraries that provide an updated travel path to the destination…; paragraphs 0103, 0106, 0148, 0172, 0228).
Courtney is directed towards systems and methods for service facilitation for multi-modal services. Gulati describes a system for dynamic transportation planning. Therefore, they are deemed to be analogous as they both are directed towards transportation service management systems. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Courtney with Gulati because the references are analogous art because they are both directed to solutions for transportation services, which falls within applicant’s field of endeavor (system and method for transportation services), and because modifying Courtney to include Gulati’s features for including wherein the adjustment action is configured to counteract a negative quality measurement subtracted from a predicted overall service score or emphasize a positive quality measurement added to the predicted overall service score, wherein a negative quality measurement is a weighted value of a negative user experience and a positive quality measurement is a weighted value of a positive user experience; and wherein initiating the adjustment action comprises adjusting the multi-modal transportation itinerary, in the manner claimed, would serve the motivation of providing accurate transit itineraries to client devices (Gulati at paragraph 0038); and further obvious because the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
While the Courtney-Gulati combination describes ranking the alternative itineraries based on the overall score (Gulati, paragraph 0169), the Courtney-Gulati combination does not explicitly teach wherein initiating the adjustment action comprises adjusting the multi-modal transportation itinerary based on the predicted overall service score. However, Kline in the analogous art of multi-mode transportation planning systems teaches this concept. Kline teaches:
wherein initiating the adjustment action comprises adjusting the multi-modal transportation itinerary based on the predicted overall service score (paragraph 0003, discussing that the method, computer program product and computer system can generate a confidence score for the user traveling along generated route based on the received user data. The method, computer program product and computer system can, responsive to determining the confidence score is below a confidence level threshold, modify the generated route based on an analysis of the generated route at the specific point, wherein the modified route causes the confidence score to increase above the confidence level threshold; paragraph 0017, discussing that the multi-mode transportation program can utilize the received user data to generate a confidence score for the user along the route and if multi-mode transportation program determines the destination location has not been reached, multi-mode transportation program can determine whether the confidence score is above a pre-defined threshold. Responsive to multi-mode transportation program determining the confidence score is not above a pre-defined threshold, multi-mode transportation program can modify the generated route to increase the confidence score and display guidance for the modified route; paragraph 0036, discussing that the multi-mode transportation program utilizes an algorithm to calculate a confidence score utilizing the received user data and a weighted scale for each of the subsets of the received user data. For each subset of the received user data, multi-mode transportation program can utilize a plurality of data ranges and assign a value to each of the plurality of data ranges when generating a confidence score; paragraph 0036, discussing that the multi-mode transportation program compiles all the values for all the subsets of the received user data and generates the confidence score for the user via the sum of all the values; paragraph 0043, discussing that while the user is traveling in the personal vehicle, multi-mode transportation program receives user data, generates a confidence score, and determines the confidence score is no longer above the confidence score threshold. Multi-mode transportation program analyzes the generated route and determines the user proceeded to enter a highway road from a local road in the person vehicle. Multi-mode transportation program modifies the generated route by instructing the user to exit at next exit ramp to avoid portion 308, where portion 308 represents a remaining highway road portion of the previously generated route).
The Courtney-Gulati combination describes features related to facilitating multi-modal services. Kline describes a system for multi-mode route selection. Therefore, they are deemed to be analogous as they both are directed towards transportation service management systems. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the Courtney-Gulati combination with Kline because the references are analogous art because they are both directed to solutions for transportation services, which falls within applicant’s field of endeavor (system and method for transportation services), and because modifying the Courtney-Gulati combination to include Kline’s feature for including wherein initiating the adjustment action comprises adjusting the multi-modal transportation itinerary based on the predicted overall service score, in the manner claimed, would serve the motivation of modifying the generated route to increase the score (Kline at paragraph 0017); and further obvious because the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
As per claim 2, the Courtney-Gulati-Kline combination teaches the computer-implemented method of claim 1. Courtney further teaches wherein the other transportation leg comprises a ground transportation service for the user, and wherein the adjustment action comprises at least one of: (i) initiating an adjustment to the ground transportation for the user; or (ii) initiating an increase in a priority associated with the user for the ground transportation (paragraph 0048, discussing that by way of example, the service entity computing system can generate the modified multi-modal transportation itinerary(s) by determining one or more multi-modal transportation itinerary(s) affected by the deviation. The affected multi-modal transportation itinerary(s), for example, can include multi-modal transportation itinerary(s) with an aerial transportation leg associated with an unavailable aerial vehicle. The service entity computing system can obtain one or more additional flight itineraries and/or any other flight data indicative of one or more available aerial vehicles and, based on this data, modify the aerial transportation leg of the affected multi-modal transportation itinerary(s). This can include replacing the aerial transportation leg with an available aerial vehicle, a vehicle of another modality (e.g., book another ground transportation vehicle, extend the first transportation leg to cover the second transportation leg, etc.) [i.e., This shows initiating an adjustment to the ground transportation for the user], etc.).
As per claim 3, the Courtney-Gulati-Kline combination teaches the computer-implemented method of claim 2. Courtney further teaches wherein adjusting the ground transportation for the user comprises at least one of: (i) assigning a different ground vehicle to the user; (ii) changing a service level associated with the ground transportation for the user; or (iii) changing a service type associated with the ground transportation (paragraph 0048, discussing that by way of example, the service entity computing system can generate the modified multi-modal transportation itinerary(s) by determining one or more multi-modal transportation itinerary(s) affected by the deviation. The affected multi-modal transportation itinerary(s), for example, can include multi-modal transportation itinerary(s) with an aerial transportation leg associated with an unavailable aerial vehicle. The service entity computing system can obtain one or more additional flight itineraries and/or any other flight data indicative of one or more available aerial vehicles and, based on this data, modify the aerial transportation leg of the affected multi-modal transportation itinerary(s). This can include replacing the aerial transportation leg with an available aerial vehicle, a vehicle of another modality (e.g., book another ground transportation vehicle, extend the first transportation leg to cover the second transportation leg, etc.), etc.).
As per claim 5, the Courtney-Gulati-Kline combination teaches the computer-implemented method of claim 1. Courtney further teaches wherein the other transportation leg comprises an aerial transportation service for the user, and wherein the adjustment action comprises at least one of: (i) initiating an adjustment of a seat for the user on an aircraft to be used for the aerial transportation service; or (ii) initiating an assignment of the user to a different aircraft for the aerial transportation service (paragraph 0025, discussing that the service entity computing system can create an end-to-end multi-modal itinerary that includes two or more transportation legs that include travel via two or more different transportation modalities such as, for example: cars, light electric vehicles, buses, trains, aircraft, watercraft, and/or other transportation modalities; paragraph 0041, discussing that each multi-modal transportation service can include at least two transportation legs. At least one of the at least two transportation legs can be facilitated by at least one of the one or more aerial transportation services (e.g., via a flight itinerary of the one or more flight schedules or scheduled based on the flight data); paragraph 0048, discussing that by way of example, the service entity computing system can generate the modified multi-modal transportation itinerary(s) by determining one or more multi-modal transportation itinerary(s) affected by the deviation. The affected multi-modal transportation itinerary(s), for example, can include multi-modal transportation itinerary(s) with an aerial transportation leg associated with an unavailable aerial vehicle. The service entity computing system can obtain one or more additional flight itineraries and/or any other flight data indicative of one or more available aerial vehicles and, based on this data, modify the aerial transportation leg of the affected multi-modal transportation itinerary(s). This can include replacing the aerial transportation leg with an available aerial vehicle [i.e., This shows initiating an assignment of the user to a different aircraft for the aerial transportation service], a vehicle of another modality (e.g., book another ground transportation vehicle, extend the first transportation leg to cover the second transportation leg, etc.), etc.; paragraph 0079, discussing that the service entity computing system can continually re-evaluate various itineraries before and even during completion of a selected itinerary. If an improved itinerary becomes available (e.g., which may include changing from a single-modal itinerary to a multi-modal itinerary if, for example, a seat on a flight becomes available) the service entity computing system can suggest the improved itinerary for selection by the rider. In some implementations, if the rider selects, via the rider computing device(s), the improved itinerary during completion of an existing itinerary, the service entity computing system can facilitate switching to the updated itinerary, including, for example, re-routing a service provider that is currently transporting the rider to an alternative, updated destination; paragraph 0113, discussing that the multi-modal transportation itinerary can include a first ground transportation leg from the origin location to a first aerial transportation facility, an aerial transportation leg from the first aerial transportation facility to a second aerial transportation facility, and a second ground transportation leg; paragraph 0059).
As per claim 6, the Courtney-Gulati-Kline combination teaches the computer-implemented method of claim 1. Courtney further teaches wherein computing the quality measurement of the multi-modal transportation service based on the state of the user comprises: accessing data associated with the multi-modal transportation service, wherein the data associated with the multi-modal transportation services comprises at least one of timing data, movement data, data associated with another user, or event data received from at least one of a plurality of distributed computing devices associated with the multi-modal transportation service (paragraph 0079, discussing that the service entity computing system can continually re-evaluate various itineraries before and even during completion of a selected itinerary. If an improved itinerary becomes available the service entity computing system can suggest the improved itinerary for selection by the rider. In some implementations, if the rider selects, via the rider computing device(s), the improved itinerary during completion of an existing itinerary, the service entity computing system can facilitate switching to the updated itinerary, including, for example, re-routing a service provider that is currently transporting the rider to an alternative, updated destination; paragraph 0093, discussing that the monitoring and mitigation system can perform monitoring of rider itineraries and can perform mitigation when an itinerary is subject to significant delay [i.e., timing data]. Thus, the monitoring and mitigation system can perform situation awareness, advisories, adjustments, and the like. The monitoring and mitigation system can trigger alerts and actions sent to the systems or devices. For example, entities such as riders, service providers, and/or operations personnel can be alerted when a certain transportation plan has been modified and can be provided with an updated plan/course of action. Thus, the monitoring and mitigation system can have additional control over the movement of aerial vehicles, ground vehicles, air traffic controllers, pilots, and rider; paragraph 0090, discussing a state monitoring service to maintain data descriptive of a current state of the world. For example, the world state system can generate, collect, and/or maintain data descriptive of planned itineraries; pre-determined transportation plans and assignments; current requests; current ground transportation service providers; current aerial transport facility operational statuses; current aerial vehicle statuses; current pilot statuses; current flight states and trajectories; current airspace information; current weather conditions; current communication system behavior/protocols; and/or the like); and
computing the quality measurement of the multi-modal transportation service based on the state of the user and the data associated with the multi-modal transportation service (paragraph 0023, discussing that during the operational time period, the service entity computing system can determine a deviation from the number of aerial vehicles. In response, the service entity computing system can generate modified multi-modal transportation itineraries to compensate for the deviation and one or more deviation offset(s) to offset inefficiencies of the modified multi-modal transportation itineraries to the aerial vehicle provider; paragraph 0093, discussing that the monitoring and mitigation system can perform monitoring of rider itineraries and can perform mitigation when an itinerary is subject to significant delay (e.g., one of the legs fails to succeed). Thus, the monitoring and mitigation system can perform situation awareness, advisories, adjustments, and the like. The monitoring and mitigation system can trigger alerts and actions sent to the systems or devices. For example, entities such as riders, service providers, and/or operations personnel can be alerted when a certain transportation plan has been modified and can be provided with an updated plan/course of action. Thus, the monitoring and mitigation system can have additional control over the movement of aerial vehicles, ground vehicles, air traffic controllers, pilots, and riders).
Claim 14 recites substantially similar limitations that stand rejected via the art citations and rationale applied to claim 1, as discussed above. Further, as per claim 14, the Courtney-Gulati-Kline combination teaches one or more non-transitory, computer-readable media storing instructions that are executable by one or more processors to cause the one or more processors to perform operations (Courtney, paragraph 0005: “The computing system includes one or more processors and one or more tangible, non-transitory, computer readable media that collectively store instructions that when executed by the one or more processors cause the computing system to perform operations. The operations include obtaining multi-modal transportation service data indicative of a plurality of multi-modal transportation services).
As pr claim 15, the Courtney-Gulati-Kline combination teaches the one or more non-transitory, computer-readable media of claim 14. Courtney further teaches wherein the user is associated with a user device configured to run a software application associated with the transportation service (paragraph 0060, discussing that the computing device(s) can also include a communication interface used to communicate with one or more other system(s). The communication interface can include any circuits, components, software, etc. for communicating via one or more networks. In some implementations, the communication interface can include for example, one or more of a communications controller, receiver, transceiver, transmitter, port, conductors, software and/or hardware for communicating data/information; paragraph 0069, discussing that the service entity computing system can be communicatively connected over a network to the vehicle provider computing system(s), one or more rider computing devices, one or more service provider computing devices for a first ground transportation leg, one or more service provider computing devices for a second ground transportation leg, one or more service provider computing devices for an Nth ground transportation leg, and/or one or more infrastructure and operations computing devices. For example, the vehicle provider computing system(s) can include one or more communication interfaces communicatively connected to the service entity computing system and the service entity computing system can include one or more communication interfaces communicatively connected to the vehicle provider computing system(s); paragraph 0075, discussing that the rider can interact with a dedicated application on the rider computing device (e.g., smartphone, tablet, wearable computing device, or the like) to initiate the request. By way of example, the rider can interact with the rider computing device by opening the dedicated application and/or initiating a booking process via the dedicated application. The service entity computing system can initiate the generation of a plurality of multi-modal transportation itineraries in response to the rider opening the dedicated application and/or otherwise initiating a booking process), and
wherein the adjustment action comprises a modification to at least one user interface of the software application (paragraph 0078, discussing that the service entity computing system can evaluate one or more itineraries that are single-modal and one or more itineraries that are multi-modal. The service entity computing system can compare the generated itineraries...For example, one or more of the best itineraries (e.g., as evaluated based on various characteristics such as cost, time, etc.) can be suggested to the rider. The rider can select, via the rider computing device, one of the suggested itineraries to receive transportation services in accordance with the selected itinerary; paragraph 0079, discussing that the service entity computing system can continually re-evaluate various itineraries before and even during completion of a selected itinerary. If an improved itinerary becomes available (e.g., which may include changing from a single-modal itinerary to a multi-modal itinerary if, for example, a seat on a flight becomes available) the service entity computing system can suggest the improved itinerary for selection by the rider. In some implementations, if the rider selects, via the rider computing device, the improved itinerary during completion of an existing itinerary, the service entity computing system can facilitate switching to the updated itinerary, including, for example, re-routing a service provider that is currently transporting the rider to an alternative, updated destination; paragraph 0075).
As per claim 16, the Courtney-Gulati-Kline combination teaches the one or more non-transitory, computer-readable media of claim 15. Courtney further teaches wherein the at least one user interface of the software application is configured to provide one or more user notifications, and wherein initiating the adjustment action comprises: accessing alternative transportation data associated with an alternative transportation service (paragraph 0093, discussing that the monitoring and mitigation system can perform monitoring of rider itineraries and can perform mitigation when an itinerary is subject to significant delay. Thus, the monitoring and mitigation system can perform situation awareness, advisories, adjustments, and the like. The monitoring and mitigation system can trigger alerts and actions sent to the systems 140 or devices 145, 150, 160, 170, and 190. For example, entities such as riders, service providers, and/or operations personnel can be alerted when a certain transportation plan has been modified and can be provided with an updated plan/course of action. Thus, the monitoring and mitigation system can have additional control over the movement of aerial vehicles, ground vehicles, air traffic controllers, pilots, and riders; paragraphs 0067, 0047, 0078);
computing a user notification descriptive of a comparison between the alternative transportation service and the multi-modal transportation service (paragraph 0079, discussing that the service entity computing system can continually re-evaluate various itineraries during completion of a selected itinerary. If an improved itinerary becomes available (e.g., which may include changing from a single-modal itinerary to a multi-modal itinerary if, for example, a seat on a flight becomes available) the service entity computing system can suggest the improved itinerary for selection by the rider. In some implementations, if the rider selects, via the rider computing device, the improved itinerary during completion of an existing itinerary, the service entity computing system can facilitate switching to the updated itinerary, including, for example, re-routing a service provider that is currently transporting the rider to an alternative, updated destination; paragraph 0093, discussing that the monitoring and mitigation system 136 can perform monitoring of rider itineraries and can perform mitigation when an itinerary is subject to significant delay. Thus, the monitoring and mitigation system can perform situation awareness, advisories, adjustments, and the like. The monitoring and mitigation system can trigger alerts and actions sent to the systems 140 or devices 145, 150, 160, 170, and 190. For example, entities such as riders, service providers, and/or operations personnel can be alerted when a certain transportation plan has been modified and can be provided with an updated plan/course of action. Thus, the monitoring and mitigation system can have additional control over the movement of aerial vehicles, ground vehicles, air traffic controllers, pilots, and rider); and
transmitting, over the network, data indicative of the user notification to the user device during the multi-modal transportation service (paragraph 0079, discussing that the service entity computing system can continually re-evaluate various itineraries during completion of a selected itinerary. If an improved itinerary becomes available (e.g., which may include changing from a single-modal itinerary to a multi-modal itinerary if, for example, a seat on a flight becomes available) the service entity computing system can suggest the improved itinerary for selection by the rider. In some implementations, if the rider selects, via the rider computing device, the improved itinerary during completion of an existing itinerary, the service entity computing system can facilitate switching to the updated itinerary, including, for example, re-routing a service provider that is currently transporting the rider to an alternative, updated destination; paragraph 0093, discussing that the monitoring and mitigation system 136 can perform monitoring of rider itineraries and can perform mitigation when an itinerary is subject to significant delay. Thus, the monitoring and mitigation system can perform situation awareness, advisories, adjustments, and the like. The monitoring and mitigation system can trigger alerts and actions sent to the systems 140 or devices 145, 150, 160, 170, and 190. For example, entities such as riders, service providers, and/or operations personnel can be alerted when a certain transportation plan has been modified and can be provided with an updated plan/course of action. Thus, the monitoring and mitigation system can have additional control over the movement of aerial vehicles, ground vehicles, air traffic controllers, pilots, and rider).
Claim 20 recites substantially similar limitations that stand rejected via the art citations and rationale applied to claim 1, as discussed above. Further, as per claim 20, the Courtney-Gulati-Kline combination teaches a computing system comprising: one or more processors; and one or more tangible, non-transitory, computer readable media that store instructions that are executable by the one or more processors to cause the computing system to perform operations (Courtney, paragraph 0005: “The computing system includes one or more processors and one or more tangible, non-transitory, computer readable media that collectively store instructions that when executed by the one or more processors cause the computing system to perform operations. The operations include obtaining multi-modal transportation service data indicative of a plurality of multi-modal transportation services.”);
wherein the multi-modal transportation itinerary comprises at least two transportation legs for providing the multi-modal transportation service (paragraph 0005: “The plurality of multi-modal transportation services are associated with one or more transportation services. Each multi-modal transportation service includes at least two transportation legs.”);
wherein the data associated with the multi-modal transportation service is indicative of a location of the user relative to the multi-modal transportation itinerary (paragraph 0045, discussing that the one or more expected transportation request attributes, for example, can include a type of requested service, a time sensitivity of the requested service, a capacity sensitivity of the requested service, one or more locations (e.g., origin, destination, etc.) associated with the requested service; paragraph 0078, discussing that the service entity computing system can evaluate the rider's current location, origin location, and/or destination location to determine which modalities of transportation are usable at such location).
32. Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Courtney in view of Gulati, in view of Kline, in further view of Hochberg et al., Pub. No.: US 2023/0140268 A1, [hereinafter Hochberg].
As per claim 4, the Courtney-Gulati-Kline combination teaches the computer-implemented method of claim 2. Although not explicitly taught by the Courtney-Gulati-Kline combination, Hochberg in the analogous art of transportation request management teaches wherein increasing the priority associated with the user for the ground transportation comprises adjusting a data structure for assigning a ground vehicle to the user to increase the priority with which the ground vehicle is assigned to the user (paragraph 0007, discussing a system for managing a fleet of vehicles; paragraph 0012, discussing that in some embodiments, there are a plurality of users and a priority among the plurality of users is determined based on predefined criteria. In some embodiments, the priority is determined after an event which caused lateness; paragraph 0014, discussing that in some embodiments, the priority of the first user is based on a medical priority of the first user, user satisfaction, or any combination thereof. In some embodiments, the priority of the first user is based on a type of ride, where the type of ride is a leisure ride, rides scheduled for treatments, emergency rides or a combination thereof. In some embodiments, the priority of the first user is modified during the trip of the first user. In some embodiments, the traffic conditions are at a time of pickup; paragraph 0017, discussing that there are a plurality of users and a priority among the plurality of users is determined based on predefined criteria. In some embodiments, the priority is determined after an event which caused lateness; paragraph 0146, discussing that it can be desirable to assign rideshare vehicles to users based on a priority. For example, in some scenarios, some riders can have a priority that is higher than other riders, such that a first user can be reassigned to a different ridesharing vehicle before being picked up and/or deprioritized on a pick-up and/or drop-off schedule a particular ridesharing vehicle in favor of a second user. In some embodiments, a first user can have a priority while a second user does not; paragraph 0151, discussing that the priority can be determined at the time of ride assignment. In some embodiments, the priority can be modified during the trip. For example, a type of ride for the first user can change in real time from a leisure ride to an emergency ride (e.g., the user's wife goes into labor). In these embodiments, the priority for the first user can change during the trip).
The Courtney-Gulati-Kline combination describes features related to facilitating multi-modal services. Hochberg discusses vehicle ridesharing and systems and methods for ridesharing management. Therefore, they are deemed to be analogous as they both are directed towards transportation service management systems. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the Courtney-Gulati-Kline combination with Hochberg because the references are analogous art because they are both directed to solutions for transportation services, which falls within applicant’s field of endeavor (system and method for transportation services), and because modifying the Courtney-Gulati-Kline combination to include Hochberg’s feature for including wherein increasing the priority associated with the user for the ground transportation comprises adjusting a data structure for assigning a ground vehicle to the user to increase the priority with which the ground vehicle is assigned to the user, in the manner claimed, would serve the motivation of facilitating other processes and functions (Hochberg at paragraph 0086); and further obvious because the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
33. Claims 7-9 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Courtney in view of Gulati, in view of Kline, in further view of Scofield et al., Pub. No.: US 2013/0046456 A1, [hereinafter Scofield].
As per claim 7, the Courtney-Gulati-Kline combination teaches the computer-implemented method of claim 6. While Courtney describes a time threshold (paragraph 0056: “A layover flight can include a flight that causes a layover under and/or over a preferred time threshold. Layover flights can include an overnight layover that violates a layover preference of a vehicle provider by exceeding a maximum time threshold.”), Courtney does not explicitly teach wherein computing the quality measurement of the multi-modal transportation service based on the state of the user and the data associated with the multi-modal transportation service comprises: accessing a time threshold associated with the user state of the user, wherein the time threshold is based on historical transportation data for the user state; computing a state waiting time for the user based on the data associated with the multi-modal transportation service, the state waiting time descriptive of a period of time that the user remains in the user state; and computing the quality measurement based on a comparison of the time threshold and the state waiting time. However, Scofield in the analogous art of systems for managing travel options teaches these concepts. Scofield teaches:
wherein computing the quality measurement of the multi-modal transportation service based on the state of the user and the data associated with the multi-modal transportation service comprises: accessing a time threshold associated with the state of the user, wherein the time threshold is based on historical transportation data for the user state (paragraph 0002, discussing techniques for assessing inter-modal passenger travel options based on multiple types of information, such as for commuter passengers who have multiple alternative travel options for a trip within a region that use multiple modes of passenger transportation; paragraph 0024, discussing that as one particular illustrative example, consider a user commute in which one alternative travel option includes using a particular bus route for a majority of the trip, and this travel option is in many circumstances faster and cheaper than making the trip by private vehicle. However, some or all of the benefits of this travel option may disappear if parking is not available in a parking lot near a bus stop that the user would use for the bus route, as the time and cost of using this travel option may greatly increase if alternative manners of getting to the bus stop are used. In addition, some or all of the benefits of this travel option may disappear if the general-purpose lanes available to the user's private vehicle are not congested at a particular time and/or have low or no current tolls (e.g., for roads with variable tolling, such as based on time and/or congestion). Furthermore, some or all of the benefits of this travel option may disappear if the user's departure time will result in a long wait at the bus stop for the next bus, and may be further affected based on user preferences related to particular weather conditions (e.g., with the evaluation criteria for the travel option being based not only in part on the amount of time waiting, but also the weather conditions during the wait; paragraph 0029, discussing that the routing activities include considering one or more inter-modal travel options that each occur via multiple transportation modes during different parts of the travel between the starting and destination locations. When considering inter-modal travel options, the routing activities may include initially selecting potential mass transit embarkation/debarkation locations and associated mass transit travel modes that satisfy any specified constraints, such as a required time-of-arrival at the destination and/or a required total travel time. As a next step, the initial selected potential mass transit embarkation/debarkation locations may be filtered and excluded by using best-path calculations from a prior travel point to those mass transit locations, given information about expected current and/or future traffic conditions or other travel-related conditions, parking availability for parking locations at or near those mass transit locations, information about time-to-park at such parking locations, information about time-to-travel between such parking locations and those mass transit locations, etc. One or more resulting alternative travel options that are determined to be viable with respect to any timing-related constraints may be further evaluated with respect to other constraints and/or evaluation criteria, including to use assessed road traffic condition information when appropriate to evaluate likely travel times and optionally travel time variability and/or certainty associated with the travel. For example, a total monetary cost associated with each alternative travel option may be determined, and optionally used to filter or otherwise remove an alternative travel option if it exceeds a maximum threshold...In addition to, or instead of a total monetary cost, a total travel time cost associated with each alternative travel option may be determined, and optionally used to filter or otherwise remove an alternative travel option if it exceeds a maximum threshold; paragraph 0033, discussing that the IMTOA system may perform various additional operations. For example, when identifying and initially selecting intermodal travel access points to use in determining candidates for alternative travel options, the IMTOA system may in some embodiments require that one or more intermodal travel access points be considered (e.g., based on user instructions or preferences) and/or give preferences to or exclude some such intermodal travel access points (e.g., based on one or more factors, including by falling above or below a defined threshold for the factors, such as travel time to reach, distance to reach, confidence or variability in travel time to reach, confidence or variability in travel time to use the resulting mass transit option, degree that travel using the mass transit option heads toward the destination, parking availability, ease of access, etc., and more generally based on user instructions or preferences); paragraph 0048, discussing that the operations of the IMTOA system may be performed in various manners in various embodiments. In some embodiments and situations, the IMTOA system may perform some or all of its activities in a manner specific to one or more particular users (e.g., in response to a request from those users), including to optionally use user-specific constraints, preferences and associated travel-related information (e.g., information about one or more personal vehicles of the user, information about one or more travel-related capabilities of the user, information about historical trips of the user, etc.); paragraph 0060, discussing that the determining one or more alternative travel options may be performed in various manners, including based in part on user input, on historical user trips, on routing algorithms that consider multiple available transportation modes, etc., including to filter and exclude possible travel options that are not viable with respect to specified constraints; paragraph 0047, 0052, 0057);
computing a state waiting time for the user based on the data associated with the multi-modal transportation service, the state waiting time descriptive of a period of time that the user remains in the user state (paragraph 0024, discussing that as one particular illustrative example, consider a user commute in which one alternative travel option includes using a particular bus route for a majority of the trip, and this travel option is in many circumstances faster and cheaper than making the trip by private vehicle. However, some or all of the benefits of this travel option may disappear if parking is not available in a parking lot near a bus stop that the user would use for the bus route, as the time and cost of using this travel option may greatly increase if alternative manners of getting to the bus stop are used. In addition, some or all of the benefits of this travel option may disappear if the general-purpose lanes available to the user's private vehicle are not congested at a particular time and/or have low or no current tolls (e.g., for roads with variable tolling, such as based on time and/or congestion). Furthermore, some or all of the benefits of this travel option may disappear if the user's departure time will result in a long wait at the bus stop for the next bus, and may be further affected based on user preferences related to particular weather conditions (e.g., with the evaluation criteria for the travel option being based not only in part on the amount of time waiting, but also the weather conditions during the wait); and
computing the quality measurement based on a comparison of the time threshold and the state waiting time (paragraph 0023, discussing that the IMTOA system automatically determines, assesses and/or provide various types of trip-related information, including information about multiple alternative inter-modal passenger travel options for a trip, so as to enable various benefits. In many situations, a user may already have information about alternative travel options for a trip from a starting point to a destination, but may lack useful information about how such alternative travel options will compare under actual current conditions or expected conditions in the near future. For example, many users performing their daily commute are aware of several alternative travel options for the trip (e.g., multiple alternative vehicle routes for some or all of the trip, one or more mass transit options for some or all of the trip, etc.), and attempt to select the travel option that they believe is likely to be best given, at best, limited information about current conditions or likely future conditions; paragraph 0083, discussing a Travel Option Assessor routine. The routine may be provided by, for example, execution of an embodiment of the Travel Option Assessor module 166 of FIG. 1, such as to receive information about one or more candidate travel options and to assess them with respect to one or more evaluation criteria, such as enable cost-based comparisons between different candidate travel options (e.g., with respect to one or more of monetary cost, time delay cost, etc.), or to otherwise enable a particular candidate travel option to be assessed (e.g., based on a comparison to normal or typical, based on an assessed value with respect to a particular evaluation criteria such as cost or time, etc.)... In addition, the routine receives an indication of a particular candidate travel option and assesses it with respect to one or more evaluation criteria, although in other embodiments the routine may instead receive multiple candidate travel options and assess them simultaneously with respect to the same or different one or more evaluation criteria.).
The Courtney-Gulati-Kline combination describes features related to facilitating multi-modal services. Scofield discusses a method for assessing inter-modal passenger travel options. Therefore, they are deemed to be analogous as they both are directed towards transportation service management systems. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the Courtney-Gulati-Kline combination with Scofield because the references are analogous art because they are both directed to solutions for transportation services, which falls within applicant’s field of endeavor (system and method for transportation services), and because modifying the Courtney-Gulati-Kline combination to include Scofield’s features for including wherein computing the quality measurement of the multi-modal transportation service based on the state of the user and the data associated with the multi-modal transportation service comprises: accessing a time threshold associated with the state of the user, wherein the time threshold is based on historical transportation data for the user state; computing a state waiting time for the user based on the data associated with the multi-modal transportation service, the state waiting time descriptive of a period of time that the user remains in the user state; and computing the quality measurement based on a comparison of the time threshold and the state waiting time, in the manner claimed, would serve the motivation of enabling improved user travel (Scofield at paragraph 0035); and further obvious because the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
As per claim 8, the Courtney-Gulati-Kline-Scofield combination teaches the computer-implemented method of claim 7. Courtney further teaches wherein the user is associated with one or more user characteristics (paragraph 0045, discussing that the multi-modal transportation services data can include itinerary data indicative of a number of services expected to be requested during the operational time period and/or one or more expected transportation request attributes of each of the expected service requests. The one or more expected transportation request attributes, for example, can include a type of requested service (e.g., single passenger transportation, group passenger transportation, item transportation, etc.), a time sensitivity of the requested service, a capacity sensitivity of the requested service, one or more locations associated with the requested service, etc.).
Courtney does not explicitly teach wherein the time threshold associated with the user state is based the one or more user characteristics. However, Scofield in the analogous art of systems for managing travel options teaches these concepts. Scofield teaches:
wherein the time threshold associated with the user state is based the one or more user characteristics (paragraph 0029, discussing that in addition to, or instead of a total monetary cost, a total travel time cost associated with each alternative travel option may be determined, and optionally used to filter or otherwise remove an alternative travel option if it exceeds a maximum threshold--such total monetary costs may be generated in a manner relative to other alternative travel options or an indicated amount of time or that passes an indicated destination arrival time (e.g., a travel time cost based on a travel time that exceeds the shortest travel time of any of the alternative travel options or that exceeds another indicated time or indicated amount of time), and/or may be generated in an absolute manner (e.g., a total amount of travel time, an estimated arrival time at the destination, etc.). Furthermore, if any other user-specified constraints have been gathered, they may be similarly used to filter any alternative travel options that do not satisfy those constraints (e.g., based on weather conditions, disallowed travel modes, etc.); paragraph 0033, discussing that in addition, the IMTOA system may in some embodiments perform various additional operations. For example, when identifying and initially selecting intermodal travel access points (e.g., mass transit embarkation/debarkation locations) to use in determining candidates for alternative travel options, the IMTOA system may in some embodiments require that one or more intermodal travel access points be considered (e.g., based on user instructions or preferences) and/or give preferences (positive and/or negative) to or exclude some such intermodal travel access points (e.g., based on one or more factors, including by falling above or below a defined threshold for the factors, such as travel time to reach, distance to reach, confidence or variability in travel time to reach, confidence or variability in travel time to use the resulting mass transit option, degree that travel using the mass transit option heads toward the destination, parking availability, ease of access, etc., and more generally based on user instructions or preferences…).
The Courtney-Gulati-Kline combination describes features related to facilitating multi-modal services. Scofield discusses a method for assessing inter-modal passenger travel options. Therefore, they are deemed to be analogous as they both are directed towards transportation service management systems. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the Courtney-Gulati-Kline combination with Scofield because the references are analogous art because they are both directed to solutions for transportation services, which falls within applicant’s field of endeavor (system and method for transportation services), and because modifying the Courtney-Gulati-Kline combination to include Scofield’s feature for including wherein the time threshold associated with the user state is based the one or more user characteristics, in the manner claimed, would serve the motivation of enabling improved user travel (Scofield at paragraph 0035); and further obvious because the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
As per claim 9, the Courtney-Gulati-Kline-Scofield combination teaches the computer-implemented method of claim 7. Although not explicitly taught by Courtney, Scofield in the analogous art of systems for managing travel options teaches wherein the time threshold associated with the user state is based on a geographic region associated with the multi-modal transportation service (paragraph 0012, discussing that some aspects are introduced regarding road traffic information that may be available for use by the IMTOA system in at least some embodiments. In particular, such available road traffic information may have various forms. For example, in some embodiments, available road traffic information may include historical traffic data that reflects information about traffic for various target roads of interest in a geographical area, such as for a network of roads in the geographic area. In addition, in some embodiments, the available road traffic information may include current traffic data and/or automatically determined predicted future traffic data. Furthermore, various road traffic information may be obtained in various manners, such as from stationary road traffic sensors and/or from mobile data sources (e.g., a series of data samples that are obtained from a vehicle or other mobile data source that is currently or recently engaged in a trip over particular roads, such as with each data sample including an associated road location and time). Moreover, such data readings and data samples may be filtered, conditioned and/or aggregated in various ways before further use; paragraph 0015, discussing that traffic information is tracked and/or determined for each of multiple geographic areas , with each geographic area having a network of multiple inter-connected roads. Such geographic areas may be selected in various ways, such as based on areas in which traffic data is readily available (e.g., based on networks of road sensors for at least some of the roads in the area), in which particular other types of transportation modes are available, in which traffic congestion is a significant problem, and/or in which a high volume of road traffic occurs during at least some times. In some such embodiments, the roads for which traffic information is tracked and/or determined may be based at least in part on one or more other factors, or instead information may be tracked and/or determined for all roads).
The Courtney-Gulati-Kline combination describes features related to facilitating multi-modal services. Scofield discusses a method for assessing inter-modal passenger travel options. Therefore, they are deemed to be analogous as they both are directed towards transportation service management systems. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the Courtney-Gulati-Kline combination with Scofield because the references are analogous art because they are both directed to solutions for transportation services, which falls within applicant’s field of endeavor (system and method for transportation services), and because modifying the Courtney-Gulati-Kline combination to include Scofield’s feature for including wherein the time threshold associated with the user state is based on a geographic region associated with the multi-modal transportation service, in the manner claimed, would serve the motivation of enabling improved user travel (Scofield at paragraph 0035); and further obvious because the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
As per claim 11, the Courtney-Gulati-Kline combination teaches the computer-implemented method of claim 10. Although not explicitly taught by Courtney, Scofield in the analogous art of systems for managing travel options teaches wherein computing the predicted overall service score for the multi-modal transportation service comprises: determining a weighted quality measurement based on the user state (paragraph 0029, discussing that in addition to, or instead of a total monetary cost, a total travel time cost associated with each alternative travel option may be determined, and optionally used to filter or otherwise remove an alternative travel option if it exceeds a maximum threshold--such total monetary costs may be generated in a manner relative to other alternative travel options or an indicated amount of time or that passes an indicated destination arrival time (e.g., a travel time cost based on a travel time that exceeds the shortest travel time of any of the alternative travel options or that exceeds another indicated time or indicated amount of time), and/or may be generated in an absolute manner (e.g., a total amount of travel time, an estimated arrival time at the destination, etc.). Furthermore, if any other user-specified constraints have been gathered, they may be similarly used to filter any alternative travel options that do not satisfy those constraints (e.g., based on weather conditions, disallowed travel modes, etc.); paragraph 0030, discussing that After one or more viable alternative travel options are determined for the trip, the IMTOA system may further perform automated activities to assess those travel options with respect to one or more evaluation criteria, including to identify one or more preferred alternative travel options (e.g., a `best` alternative travel option with respect to the one or more evaluation criteria). As one example, the IMTOA system may in some embodiments and situations identify a lowest cost preferred alternative travel option and a lowest travel time preferred alternative travel option. More generally, the IMTOA system may use any gathered evaluation criteria for the assessment, including any gathered user preference information (e.g., optionally weighted in a user-specified manner or an automatically determined manner); and
computing the predicted overall service score based on the weighted quality measurement (paragraph 0029, discussing that in addition to, or instead of a total monetary cost, a total travel time cost associated with each alternative travel option may be determined, and optionally used to filter or otherwise remove an alternative travel option if it exceeds a maximum threshold--such total monetary costs may be generated in a manner relative to other alternative travel options or an indicated amount of time or that passes an indicated destination arrival time (e.g., a travel time cost based on a travel time that exceeds the shortest travel time of any of the alternative travel options or that exceeds another indicated time or indicated amount of time), and/or may be generated in an absolute manner (e.g., a total amount of travel time, an estimated arrival time at the destination, etc.). Furthermore, if any other user-specified constraints have been gathered, they may be similarly used to filter any alternative travel options that do not satisfy those constraints (e.g., based on weather conditions, disallowed travel modes, etc.); paragraph 0030, discussing that After one or more viable alternative travel options are determined for the trip, the IMTOA system may further perform automated activities to assess those travel options with respect to one or more evaluation criteria, including to identify one or more preferred alternative travel options (e.g., a `best` alternative travel option with respect to the one or more evaluation criteria). As one example, the IMTOA system may in some embodiments and situations identify a lowest cost preferred alternative travel option and a lowest travel time preferred alternative travel option. More generally, the IMTOA system may use any gathered evaluation criteria for the assessment, including any gathered user preference information (e.g., optionally weighted in a user-specified manner or an automatically determined manner; paragraph 0033, discussing that in addition, the IMTOA system may in some embodiments perform various additional operations. For example, when identifying and initially selecting intermodal travel access points (e.g., mass transit embarkation/debarkation locations) to use in determining candidates for alternative travel options, the IMTOA system may in some embodiments require that one or more intermodal travel access points be considered (e.g., based on user instructions or preferences) and/or give preferences (positive and/or negative) to or exclude some such intermodal travel access points (e.g., based on one or more factors, including by falling above or below a defined threshold for the factors, such as travel time to reach, distance to reach, confidence or variability in travel time to reach, confidence or variability in travel time to use the resulting mass transit option, degree that travel using the mass transit option heads toward the destination, parking availability, ease of access, etc., and more generally based on user instructions or preferences…).
The Courtney-Gulati-Kline combination describes features related to transportation services. Scofield discusses a method for assessing inter-modal passenger travel options. Therefore, they are deemed to be analogous as they both are directed towards transportation service management systems. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the Courtney-Gulati-Kline combination with Scofield because the references are analogous art because they are both directed to solutions for transportation services, which falls within applicant’s field of endeavor (system and method for transportation services), and because modifying the Courtney-Gulati-Kline combination to include Scofield’s features for wherein computing the predicted overall service score for the multi-modal transportation service comprises: determining a weighted quality measurement based on the user state and computing the predicted overall service score based on the weighted quality measurement, in the manner claimed, would serve the motivation of enabling improved user travel (Scofield at paragraph 0035); and further obvious because the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
34. Claims 10 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Courtney in view of Gulati, in view of Kline, in further view of Tian et al., Pub. No.: US 2021/0075792 A1, [hereinafter Tian].
As per claim 10, the Courtney-Gulati-Kline combination teaches the computer-implemented method of claim 1. Although not explicitly by Courtney, Tian in the analogous art of multi-modal transportation service planning teaches wherein determining the adjustment action associated with the multi-modal transportation itinerary for the user based on the quality measurement comprises: computing the predicted overall service score for the multi-modal transportation service based on the quality measurement, wherein the predicted overall service score is indicative of a predicted quality of the multi-modal transportation service across a plurality of states of the multi-modal transportation service (paragraph 0002, discussing systems and methods for real-time planning and fulfillment of multi-modal transportation services; paragraph 0044, discussing that the computing system can select one or more of the “best” itineraries to provide for display to the user. As one example, to determine which itineraries are the “best”, the computing system can score each itinerary using an objective function that balances various factors such as: total travel time; cumulative cost to the service providers to provide the various legs of the itinerary; price to the user to have the service provided; deviation of estimated arrival time from the requested arrival time; deviation of the estimated departure time from the requested departure time; satisfaction of desired vehicle characteristics; number and/or quality of contingency plans; and/or various other measures of itinerary quality; paragraph 0045, discussing that the computing system can assess the number and/or quality of contingency plans associated with a given itinerary. For example, contingency plans can include alternative transportation legs that, should a particular transportation leg of an itinerary fail to be successfully completed as planned, the user can alternatively use to arrive at their destination. In some implementations, to understand the number and/or quality of contingency plans associated with a given itinerary, the computing system can determine, for each candidate transportation leg different included in the candidate itinerary, the number and/or quality of alternative, contingency transportation legs available between a first location and a second location associated with the candidate transportation leg; paragraph 0046, discussing that to provide an example, a first candidate itinerary may include a planned flight between Transportation Node A and Transportation Node B at 7:30 am while a second candidate itinerary may include a planned flight between Transportation Node C and Transportation Node B at 7:32 am. While Transportation Node C may be slightly closer to the user's origin than Transportation Node A and therefore enable the user to save 4 minutes total, there may be significantly more planned flights between Transportation Node A and Transportation Node B than between Transportation Node C and Transportation Node B. For example, flights may be planned between Transportation Node A and Transportation Node B every 10 minutes between 7:30 am and 8 am (e.g., 7:30, 7:40, 7:50, 8:00) while the next planned flight between Transportation Node C and Transportation Node B after the 7:32 am departure is not planned to depart until 8:15 am. Thus, there are significantly more and higher quality contingency plans associated with the planned flight between Transportation Nodes A and B relative to the planned flight between Transportation Nodes C and B. This information can be included in the assessment of the candidate itineraries. To continue the example, although the itinerary that includes use of Transportation Node C enables the user to save 4 minutes, the itinerary that includes Transportation Node A may, in some instances, be adjudged to be the better itinerary due to the number and quality of contingency plans. This outcome may be particularly true if ground transportation between the user's origin and Transportation Node C has significant variance or is known to experience delays. Thus, uncertainty and/or observed variance regarding the reliability/outcomes of certain legs of an itinerary can also be used as an input to scoring candidate itineraries; paragraph 0047, discussing that the computing system can analyze the candidate itineraries to select one or more itineraries that are high quality according to various measures); and
determining the adjustment action based on the predicted overall service score, wherein the adjustment action is configured to impact a final overall service score (paragraph 0046, discussing that to provide an example, a first candidate itinerary may include a planned flight between Transportation Node A and Transportation Node B at 7:30 am while a second candidate itinerary may include a planned flight between Transportation Node C and Transportation Node B at 7:32 am. While Transportation Node C may be slightly closer to the user's origin than Transportation Node A and therefore enable the user to save 4 minutes total, there may be significantly more planned flights between Transportation Node A and Transportation Node B than between Transportation Node C and Transportation Node B. For example, flights may be planned between Transportation Node A and Transportation Node B every 10 minutes between 7:30 am and 8 am (e.g., 7:30, 7:40, 7:50, 8:00) while the next planned flight between Transportation Node C and Transportation Node B after the 7:32 am departure is not planned to depart until 8:15 am. Thus, there are significantly more and higher quality contingency plans associated with the planned flight between Transportation Nodes A and B relative to the planned flight between Transportation Nodes C and B. This information can be included in the assessment of the candidate itineraries. To continue the example, although the itinerary that includes use of Transportation Node C enables the user to save 4 minutes, the itinerary that includes Transportation Node A may, in some instances, be adjudged to be the better itinerary due to the number and quality of contingency plans. This outcome may be particularly true if ground transportation between the user's origin and Transportation Node C has significant variance or is known to experience delays. Thus, uncertainty and/or observed variance regarding the reliability/outcomes of certain legs of an itinerary can also be used as an input to scoring candidate itineraries; paragraph 0047, discussing that the computing system can analyze the candidate itineraries to select one or more itineraries that are high quality according to various measures. The computing system can present the one or more itineraries to the user (e.g., via a user interface on the user's computing device), along with additional information such as a single end-to-end price to fulfill the itinerary. For example, the single price can be the sum of the prices for each leg of the itinerary which may each be computed using various techniques, including, for example, fixed pricing and/or dynamic or “surge” pricing. The user can choose to request fulfillment of an itinerary, decline fulfillment (e.g., by taking no action), or can modify one or more characteristics of the request. For example, the user can modify the itinerary by indicating that the user is electing to complete one of the transportation legs by walking on associated with the candidate transportation leg; paragraph 0061, discussing that the user interface can provide warnings or other indications of how certain mitigation activities or potential actions might affect other users of the system. For example, if the mitigation personnel attempts to delay a not-yet-departed transportation plan (e.g., flight plan) to wait for the delayed user, the user interface can inform the mitigation personnel that such action would impact 3 other travelers. The warnings/indications provided in the user interface can provide impact information according to various metrics including, for each available choice/action, a number of users that will be impacted as a result of the choice/action, a number of users that will miss their arrive by times as a result of the choice/action, an aggregate number of minutes that will be added to all the users' transportation services as a result of the choice/action, and/or other metrics. Generally, preference can be given to mitigation strategies that have minimal impacts on other users; paragraph 0151, discussing providing the human mitigation personnel with indicators that describe one or more impacts of one or more potential actions available to the human mitigation personnel within the mitigation user interface).
The Courtney-Gulati-Kline combination describes features related to facilitating multi-modal services. Tian discusses multi-modal transportation service planning and fulfillment. Therefore, they are deemed to be analogous as they both are directed towards transportation service management systems. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the Courtney-Gulati-Kline combination with Tian because the references are analogous art because they are both directed to solutions for transportation services, which falls within applicant’s field of endeavor (system and method for transportation services), and because modifying the Courtney-Gulati-Kline combination to include Tian’s features for including wherein determining the adjustment action associated with the multi-modal transportation itinerary for the user based on the quality measurement comprises: computing the predicted overall service score for the multi-modal transportation service based on the quality measurement, wherein the predicted overall service score is indicative of a predicted quality of the multi-modal transportation service across a plurality of states of the multi-modal transportation service; and determining the adjustment action based on the predicted overall service score, wherein the adjustment action is configured to impact a final overall service score, in the manner claimed, would serve the motivation of facilitating multi-modal transportation services for riders (Tian at paragraph 0002); and further obvious because the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
As per claim 12, the Courtney-Gulati-Kline combination teaches the computer-implemented method of claim 10. Although not explicitly by Courtney, Tian in the analogous art of multi-modal transportation service planning teaches wherein computing the predicted overall service score for the multi-modal transportation service comprises: accessing one or more other quality measurements of the multi-modal transportation service for one or more other states of the user relative to the multi-modal transportation itinerary (paragraph 0002, discussing systems and methods for real-time planning and fulfillment of multi-modal transportation services; paragraph 0044, discussing that the computing system can select one or more of the “best” itineraries to provide for display to the user. As one example, to determine which itineraries are the “best”, the computing system can score each itinerary using an objective function that balances various factors such as: total travel time; cumulative cost to the service providers to provide the various legs of the itinerary; price to the user to have the service provided; deviation of estimated arrival time from the requested arrival time; deviation of the estimated departure time from the requested departure time; satisfaction of desired vehicle characteristics; number and/or quality of contingency plans; and/or various other measures of itinerary quality; paragraph 0045, discussing that the computing system can assess the number and/or quality of contingency plans associated with a given itinerary. For example, contingency plans can include alternative transportation legs that, should a particular transportation leg of an itinerary fail to be successfully completed as planned, the user can alternatively use to arrive at their destination. In some implementations, to understand the number and/or quality of contingency plans associated with a given itinerary, the computing system can determine, for each candidate transportation leg different included in the candidate itinerary, the number and/or quality of alternative, contingency transportation legs available between a first location and a second location associated with the candidate transportation leg; paragraph 0047, discussing that the computing system can analyze the candidate itineraries to select one or more itineraries that are high quality according to various measures; paragraph 0054, discussing that the computing system can perform the matching process for each leg of the itinerary separately and/or based on current information about the user's progress along the itinerary. In some implementations, the computing system can perform the matching process first for a most supply-constrained transportation modality (e.g., flight modality) used by the itinerary. This can ensure that the user is affirmatively matched with a service provider for the most challenging modality to match prior to transporting the user away from their initial origin (e.g., so the user does not get stuck at a transportation node without a flight waiting for them). In other implementations, there is no pre-determined order in which matching is performed but instead is based only on the respective analysis for each different transportation modality of the appropriate matching process initiation time; paragraph 0078); and
computing the predicted overall service score based on an aggregation of the quality measurement and the one or more other quality measurements of the multi-modal transportation service (paragraph 0044, discussing that the computing system can select one or more of the “best” itineraries to provide for display to the user. As one example, to determine which itineraries are the “best”, the computing system can score each itinerary using an objective function that balances various factors such as: total travel time; cumulative cost to the service providers to provide the various legs of the itinerary; price to the user to have the service provided; deviation of estimated arrival time from the requested arrival time; deviation of the estimated departure time from the requested departure time; satisfaction of desired vehicle characteristics; number and/or quality of contingency plans; and/or various other measures of itinerary quality; paragraph 0047, discussing that the computing system can analyze the candidate itineraries to select one or more itineraries that are high quality according to various measures).
The Courtney-Gulati-Kline combination describes features related to facilitating multi-modal services. Tian discusses multi-modal transportation service planning and fulfillment. Therefore, they are deemed to be analogous as they both are directed towards transportation service management systems. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the Courtney-Gulati-Kline combination with Tian because the references are analogous art because they are both directed to solutions for transportation services, which falls within applicant’s field of endeavor (system and method for transportation services), and because modifying the Courtney-Gulati-Kline combination to include Tian’s feature for including computing the predicted overall service score based on an aggregation of the quality measurement and the one or more other quality measurements of the multi-modal transportation service, in the manner claimed, would serve the motivation of facilitating multi-modal transportation services for riders (Tian at paragraph 0002); and further obvious because the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
35. Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Courtney in view of Gulati, in further view of Kline, in further view of Kumar et al., Pub. No.: US 2020/0182637 A1, [hereinafter Kumar].
As per claim 13, the Courtney-Gulati-Kline combination teaches the computer-implemented method of claim 1. Courtney further teaches wherein the state is one of a plurality of predefined user states, the plurality of predefined user states comprising a transit state and a transitional state (paragraph 0031, discussing that the service entity computing system can dynamically optimize planned transportation services by the service entity to account for real-time changes in rider availability; paragraph 0059, discussing that the service entity computing system can guarantee a capacity of a subsequent and/or early flight by booking one or more passengers for the subsequent/early flight subsequent to the non-conforming service before, during, and/or after the scheduling/performance of the non-conforming service; paragraph 0079, discussing that the service entity computing system can continually re-evaluate various itineraries during completion of a selected itinerary. If an improved itinerary becomes available the service entity computing system can suggest the improved itinerary for selection by the rider. In some implementations, if the rider selects, via the rider computing device(s), the improved itinerary during completion of an existing itinerary, the service entity computing system can facilitate switching to the updated itinerary, including, for example, re-routing a service provider that is currently transporting the rider to an alternative, updated destination; paragraph 0093, discussing that the monitoring and mitigation system can perform monitoring of rider itineraries and can perform mitigation when an itinerary is subject to significant delay (e.g., one of the legs fails to succeed). Thus, the monitoring and mitigation system can perform situation awareness, advisories, adjustments, and the like. The monitoring and mitigation system can trigger alerts and actions sent to the systems or devices. For example, entities such as riders, service providers, and/or operations personnel can be alerted when a certain transportation plan has been modified and can be provided with an updated plan/course of action. Thus, the monitoring and mitigation system can have additional control over the movement of aerial vehicles, ground vehicles, air traffic controllers, pilots, and rider).
Courtney does not explicitly teach the plurality of predefined user states comprising a boarding state, a ready state, and an arrival state. However, Kumar in the analogous art of systems for implementing multi-modal transport teaches this concept. Kumar teaches:
the plurality of predefined user states comprising a boarding state, a ready state, and an arrival state (paragraph 0067, discussing that one or more itineraries for respective legs of a journey can be booked prior to the start of the journey. Once the journey begins, the systems and methods disclosed can monitor the journey via applications such as Global Positioning System (GPS) to determine the location of the traveler at a given point in time. Various providers of the respective legs can be queried for status updates such that the itinerary is modified to account for delays. In addition, the systems and methods disclosed herein can facilitate real-time monitoring of various platforms (e.g., weather, traffic, etc.) to determine possible delays or issues that may occur during a leg. Once the itinerary is updated in real time, changes can be made to subsequent legs remaining in the journey such that the original objectives of the travel request can be approximately met (e.g., arrival time/arrival window at segment destination; paragraph 0089, discussing that once the journey is underway, progress of the traveler across modes is tracked via smartphone, vehicle location feeds, or other mechanisms. This is used along with travel conditions to continue refreshing itinerary Timelines, modifying Workflow execution to match. The system also uses the journey feed to build proprietary data around the duration of key transfer stages, such as time from airport parking to terminal, through terminal to gate, from gate to curb, from curb to rental car exit, immigration and customs; paragraph 0093, discussing that a trip is defined by the Objectives and Preferences of the traveler. Trips are described as a collection of segments, each comprised of discrete legs (e.g., leg 208a to leg 208e in FIG. 2), and each made of one or several stages. Legs are local or long-distance, and stages of a leg are either transfer or travel. Travel stages are those where primary transport occurs in a leg, while transfer stages take the traveler to or from the travel stage; paragraph 0147, discussing that another function of the MONITOR element of the system disclosed is the building of a Transfer database to enable forecasting of the pre- and post-travel stages of each M/OD (mode/origin-destination) option. Accordingly, for each M/OD option, the Transfer database maintains durations for all pre- and post-travel stages. For instance, for conventional air as Mode, the database includes durations from local mode to Origin airport, through airport to gate without checked baggage, through airport to gate with checked baggage, from gate at Destination airport to exit with checked baggage, from gate to exit without checked baggage, from exit to local mode.).
The Courtney-Gulati-Kline combination describes features related to transportation services. Kumar discusses systems and methods for implementing multi-modal transport. Therefore, they are deemed to be analogous as they both are directed towards transportation service management systems. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the Courtney-Gulati-Kline combination with Kumar because the references are analogous art because they are both directed to solutions for transportation services, which falls within applicant’s field of endeavor (system and method for transportation services), and because modifying the Courtney-Gulati-Kline combination to include Kumar’s feature for including the plurality of predefined user states comprising a boarding state, a ready state, and an arrival state, in the manner claimed, would serve the motivation of facilitating management of multi-modal travel (Kumar at paragraph 0047); and further obvious because the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
36. Claim 17 is rejected under 35 U.S.C. 103 as being unpatentable over Courtney in view of Gulati, in view of Kline, in further view of Costas et al., Pu. No.: US 2018/0285782 A1, [hereinafter Costas].
As per claim 17, the Courtney-Gulati-Kline combination teaches the one or more non-transitory, computer-readable media of claim 14. Courtney further teaches wherein the adjustment action comprises notifying an operator at an aerial facility to assist the user in transitioning between a ground transportation service to an aerial transportation service (paragraph 0049, discussing that the service entity computing system can generate a deviation offset based, at least in part, on the one or more modified itineraries and/or the one or more permissions associated with the flight data. The deviation offset, for example, can include an inefficiency associated with the one or more modified multi-modal transportation itineraries. By way of example, the deviation offset can include one or more inefficiencies associated with replacing (and/or modifying) the second transportation leg of the affected multi-modal transportation itinerary(s). The one or more inefficiencies, for example, can include an increased cost to schedule an available aerial vehicle (e.g., based on limited time, different inefficiencies associated with a different aerial vehicle provider, etc.), a cost to facilitate the availability of an aerial vehicle (e.g., servicing costs to increase the servicing (e.g., fueling, charging) speed of an aerial vehicle, downstream inefficiencies for using the aerial vehicle, overtime for an operator of the aerial vehicle, etc.), passenger inefficiencies for causing a transportation delay (e.g., a refund to a passenger issued by the service entity computing system to compensate for additional time caused by replacing an aerial transportation service with a ground transportation service, etc.), and/or any other inefficiencies associated with the modified multi-modal transportation itinerary(s); paragraph 0079, discussing that the service entity computing system can continually re-evaluate various itineraries during completion of a selected itinerary. If an improved itinerary becomes available (e.g., which may include changing from a single-modal itinerary to a multi-modal itinerary if, for example, a seat on a flight becomes available) the service entity computing system can suggest the improved itinerary for selection by the rider. In some implementations, if the rider selects, via the rider computing device, the improved itinerary during completion of an existing itinerary, the service entity computing system can facilitate switching to the updated itinerary, including, for example, re-routing a service provider that is currently transporting the rider to an alternative, updated destination; paragraph 0093, discussing that the monitoring and mitigation system can perform monitoring of rider itineraries and can perform mitigation when an itinerary is subject to significant delay. Thus, the monitoring and mitigation system can perform situation awareness, advisories, adjustments, and the like. The monitoring and mitigation system can trigger alerts and actions sent to the systems 140 or devices 145, 150, 160, 170, and 190. For example, entities such as riders, service providers, and/or operations personnel can be alerted when a certain transportation plan has been modified and can be provided with an updated plan/course of action. Thus, the monitoring and mitigation system can have additional control over the movement of aerial vehicles, ground vehicles, air traffic controllers, pilots, and rider; paragraph 0125, discussing that by way of example, the service entity computing system can generate the modified multi-modal transportation itinerary(s) by determining one or more multi-modal transportation itinerary(s) affected by the deviation. The affected multi-modal transportation itinerary(s), for example, can include multi-modal transportation itinerary(s) with an aerial transportation leg associated with the unavailable aerial vehicle. The service entity computing system can obtain one or more additional flight itineraries and/or any other flight data indicative of one or more available aerial vehicles and, based on this data, modify the aerial transportation leg of the affected multi-modal transportation itinerary(s). This can include replacing the aerial transportation leg with an available aerial vehicle, a vehicle of another modality (e.g., book another ground transportation vehicle, extend the first transportation leg to cover the second transportation leg, etc.), etc.…The service entity computing system can provide data indicative of the modified multi-modal transportation itinerary to the one or more rider computing device(s) associated with the affected multi-modal transportation itinerary(s); paragraphs 0022, 0048), and
wherein transmitting the instruction to initiate the adjustment action comprises transmitting, to a user device associated with the operator, data indicative of a notification (paragraph 0022, discussing that the vehicle request can be provided to the aerial vehicle provider and, if accepted, the computing system can perform one or more actions (e.g., booking passengers for a flight subsequent to the non-conforming service); paragraph 0079, discussing that the service entity computing system can continually re-evaluate various itineraries during completion of a selected itinerary. If an improved itinerary becomes available (e.g., which may include changing from a single-modal itinerary to a multi-modal itinerary if, for example, a seat on a flight becomes available) the service entity computing system can suggest the improved itinerary for selection by the rider. In some implementations, if the rider selects, via the rider computing device, the improved itinerary during completion of an existing itinerary, the service entity computing system can facilitate switching to the updated itinerary, including, for example, re-routing a service provider that is currently transporting the rider to an alternative, updated destination; paragraph 0093, discussing that the monitoring and mitigation system can perform monitoring of rider itineraries and can perform mitigation when an itinerary is subject to significant delay. Thus, the monitoring and mitigation system can perform situation awareness, advisories, adjustments, and the like. The monitoring and mitigation system can trigger alerts and actions sent to the systems 140 or devices 145, 150, 160, 170, and 190. For example, entities such as riders, service providers, and/or operations personnel can be alerted when a certain transportation plan has been modified and can be provided with an updated plan/course of action. Thus, the monitoring and mitigation system can have additional control over the movement of aerial vehicles, ground vehicles, air traffic controllers, pilots, and rider; paragraph 0137, discussing that the computing system can guarantee a capacity of a subsequent and/or early flight by booking one or more passengers for the subsequent/early flight subsequent to the non-conforming flight during and/or after the scheduling/performance of the non-conforming flight; paragraph 0143, discussing that the computing system can perform one or more offsetting actions to provide the offsetting attribute(s) to the aerial vehicle provider in response to receiving an acceptance of the flight request. This can include booking one or more passengers for the flight subsequent to the non-conforming flight before, during, and/or after the performance of the non-conforming flight, providing compensation for the performance of the non-conforming flight, providing a deviation offset to a deviating aerial vehicle provider, reserving and/or otherwise facilitating the use of third-party infrastructure at an unaffiliated aerial transportation facility, and/or any other action to initiate the performance of offsetting attribute(s)).
Courtney does not explicitly teach a notification to assist the user while at the aerial facility. However, Costas in the analogous art of transportation management systems teaches this concept. Costas teaches:
a notification to assist the user while at the aerial facility (paragraph 0007, discussing that when an airline expects deviations from a schedule (e.g., when a flight is being cancelled or delayed) proper assistance of passengers should be offered; paragraph 0008, discussing that updating and exchanging available data related to the flight status according to an actual passenger location through a collaborative communication channel. By doing so, enhanced assistance may be provided to passengers to help them in case of delays, missed connections, missed flights and the like; paragraph 0031, discussing that the processing unit of the system then checks the identity of the passenger prior to establishing communication with other external entities to gather information. The system also requests passenger location. Upon a valid identification, the system retrieves relevant information including flight status from several sources. A customized notification can be generated by the system according to passenger current situation and updated status of the flight. In this manner, the communication unit of the system connects to an airline data server and obtains updated information regarding the itinerary of the passenger to be collected in data storage unit. The itinerary may include the passenger name or other identifying information, the time and location of updated key events including aircraft boarding, departure, landing, and de-boarding, as well as itinerary changes requested by the passenger and those caused by airline and air-traffic events (e.g., delays, diversions, and cancelations); paragraph 0033, discussing that the system generates a customized notification to be sent to the electronic device. The notification may include likelihood of missing a flight/connection in view of updated flight information (e.g., updated flight delay information) and current passenger location…; paragraph 0055, discussing that after receiving the probability at the electronic device, the passenger may respond by notifying (acknowledging) the system that he will miss the flight. In exchange, system may offer him proper assistance (e.g., hotel accommodation, rebooking on the next available flight, etc.). Furthermore, the system can inform the airline data server that the passenger will not show up in time (passenger missing flight information). The airline may benefit from an early notification of the passenger missing the flight and may close the boarding gate without delay. Thus, airlines and ATM can take advantage of reduced turnaround times. In sum, the management of handling resources at the airport can be made more efficient; paragraph 0056, discussing that a notification is sent to the system and then relayed to the airline data server).
The Courtney-Gulati-Kline combination describes features related to transportation services. Costas discusses a computer-implemented method and system for managing passenger information. Therefore, they are deemed to be analogous as they both are directed towards transportation service management systems. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the Courtney-Gulati-Kline combination with Costas because the references are analogous art because they are both directed to solutions for transportation services, which falls within applicant’s field of endeavor (system and method for transportation services), and because modifying the Courtney-Gulati-Kline combination to include Costas’ feature for including a notification to assist the user while at the aerial facility, in the manner claimed, would serve the motivation of providing improvements to passenger assistance (Costas at paragraph 0019); and further obvious because the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
37. Claims 18 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Courtney in view of Gulati, in view of Kline, in further view of Suzuki et al., Pub. No.: US 2018/0156621 A1, [hereinafter Suzuki].
As per claim 18, the Courtney-Gulati-Kline combination teaches the one or more non-transitory, computer-readable media of claim 14. Courtney further teaches wherein the user state is one of a plurality of predefined user states (paragraph 0031, discussing that the service entity computing system can dynamically optimize planned transportation services by the service entity to account for real-time changes in rider availability; paragraph 0059, discussing that the service entity computing system can guarantee a capacity of a subsequent and/or early flight by booking one or more passengers for the subsequent/early flight subsequent to the non-conforming service before, during, and/or after the scheduling/performance of the non-conforming service; paragraph 0079, discussing that the service entity computing system can continually re-evaluate various itineraries during completion of a selected itinerary. If an improved itinerary becomes available the service entity computing system can suggest the improved itinerary for selection by the rider. In some implementations, if the rider selects, via the rider computing device(s), the improved itinerary during completion of an existing itinerary, the service entity computing system can facilitate switching to the updated itinerary, including, for example, re-routing a service provider that is currently transporting the rider to an alternative, updated destination; paragraph 0093, discussing that the monitoring and mitigation system can perform monitoring of rider itineraries and can perform mitigation when an itinerary is subject to significant delay (e.g., one of the legs fails to succeed). Thus, the monitoring and mitigation system can perform situation awareness, advisories, adjustments, and the like. The monitoring and mitigation system can trigger alerts and actions sent to the systems or devices. For example, entities such as riders, service providers, and/or operations personnel can be alerted when a certain transportation plan has been modified and can be provided with an updated plan/course of action. Thus, the monitoring and mitigation system can have additional control over the movement of aerial vehicles, ground vehicles, air traffic controllers, pilots, and rider.
Courtney does not explicitly teach wherein each respective state is associated with a corresponding weight for determining a weight quality measurement associated with the respective state. However, Suzuki in the analogous art of transportation proposal systems teaches this concept. Suzuki teaches:
wherein each respective state is associated with a corresponding weight for determining a weight quality measurement associated with the respective state (paragraph 0045, discussing that FIG. 8 is a data table listing the burden of each state for multiple users. As shown in FIG. 8, different users tend to feel burden in a common manner for the same state. Nevertheless, in this example, when comparing the burden for states “S1” to “S3” on three users allocated IDs of “ID1,”, “ID2,” and “ID3,” the order of users feeling a higher burden is “ID 3,” “ID 1,” and “ID 2.” Such slight difference between users occurs because one user may like to take trips while another may not like to take trips and feel burdensome when doing so; paragraph 0046, discussing that next, a process for estimating the trip preference with the trip preference estimation unit will be described. As illustrated in FIG. 9, the trip preference estimation unit first selects a state group when estimating the trip preference. The state group includes a plurality of states. In the example illustrated in FIG. 9, the state group includes state “S1,” state “S200,” and state “S500.” The trip preference estimation unit ranks users in order from those that feel a higher burden for each state included in the selected state group. Further, the trip preference estimation unit obtains the rank of a user in the selected state group that is subject to the trip preference estimation. Then, the trip preference estimation unit obtains the average rank in the plurality of states included in the selected state group as the trip preference for the user who is subject to the estimation. In the first embodiment, the trip preference estimation unit estimates that the trip preference of the user is high when the estimation value of the trip preference is greater than or equal to a predetermined trip preference threshold value. In contrast, when the estimation value of the trip preference is less than the predetermined trip preference threshold value, the trip preference estimation unit estimates that the trip preference of the user is moderate or low...The trip preference estimation unit may weight the ranking of the user for each state in view of the number of users compared for each of the states included in the state group and then estimate the trip preference of the user).
The Courtney-Gulati-Kline combination describes features related to transportation services. Suzuki discusses an information providing method for proposing a trip to a user. Therefore, they are deemed to be analogous as they both are directed towards transportation service management systems. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the Courtney-Gulati-Kline combination with Suzuki because the references are analogous art because they are both directed to solutions for transportation services, which falls within applicant’s field of endeavor (system and method for transportation services), and because modifying the Courtney-Gulati-Kline combination to include Suzuki’s feature for including wherein each respective state is associated with a corresponding weight for determining a weight quality measurement associated with the respective state, in the manner claimed, would serve the motivation of allowing a trip to be efficiently proposed (Suzuki at paragraph 0111); and further obvious because the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
As per claim 19, the Courtney-Gulati-Kline-Suzuki combination teaches the one or more non-transitory, computer-readable media of claim 18. Courtney further teaches wherein the operations further comprise: receiving feedback data associated with the transportation service (paragraph 0062, discussing that the one or more offsetting attributes for the non-conforming service can be determined based, at least in part, on the historical data associated with the at least one aerial vehicle provider. For example, the historical data can be indicative of one or more previous non-conforming service requests provided to the aerial vehicle provider. The one or more offsetting attributes can be determined based on an acceptance and/or rejection rate associated with one or more previous offsetting attributes corresponding to the previous non-conforming service requests and/or any other feedback data received and/or determined from previous interaction with the aerial vehicle provider; paragraph 0141).
Courtney does not explicitly teach modifying the corresponding weight of at least one respective state based on the feedback data. However, Suzuki in the analogous art of transportation proposal systems teaches this concept. Suzuki teaches:
modifying the corresponding weight of at least one respective state based on the feedback data (paragraph 0045, discussing that FIG. 8 is a data table listing the burden of each state for multiple users. As shown in FIG. 8, different users tend to feel burden in a common manner for the same state. Nevertheless, in this example, when comparing the burden for states “S1” to “S3” on three users allocated IDs of “ID1,”, “ID2,” and “ID3,” the order of users feeling a higher burden is “ID 3,” “ID 1,” and “ID 2.” Such slight difference between users occurs because one user may like to take trips while another may not like to take trips and feel burdensome when doing so; paragraph 0046, discussing that next, a process for estimating the trip preference with the trip preference estimation unit will be described. As illustrated in FIG. 9, the trip preference estimation unit first selects a state group when estimating the trip preference. The state group includes a plurality of states. In the example illustrated in FIG. 9, the state group includes state “S1,” state “S200,” and state “S500.” The trip preference estimation unit ranks users in order from those that feel a higher burden for each state included in the selected state group. Further, the trip preference estimation unit obtains the rank of a user in the selected state group that is subject to the trip preference estimation. Then, the trip preference estimation unit obtains the average rank in the plurality of states included in the selected state group as the trip preference for the user who is subject to the estimation. In the first embodiment, the trip preference estimation unit estimates that the trip preference of the user is high when the estimation value of the trip preference is greater than or equal to a predetermined trip preference threshold value. In contrast, when the estimation value of the trip preference is less than the predetermined trip preference threshold value, the trip preference estimation unit estimates that the trip preference of the user is moderate or low...The trip preference estimation unit ma y weight the ranking of the user for each state in view of the number of users compared for each of the states included in the state group and then estimate the trip preference of the user; paragraph 0063, discussing that when a response indicating that the trip proposal has not been accepted is received from at least one of the first and second users, the proposal execution unit updates the data of the degree of affinity between the first and second users and the degree of interest and the trip preference of the user who has not accepted the trip proposal as described above. Then, the proposal execution unit determines whether or not to change the trip proposal content for the user who has not accepted the trip proposal based on the data of the updated degree of affinity, the degree of interest, and the trip preference. As a result, when the trip proposal content is changed, the proposal execution unit 115 gives a new trip proposal to the user who has not accepted the trip proposal with the changed proposal content. In contrast, when the trip proposal content is not changed, the proposal execution unit instructs the proposal subject determination unit to change the person subject to the trip proposal; paragraph 0072, discussing that when determining that the trip proposal has not been accepted by at least one user based on the response data to the trip proposal, the center 100 determines whether or not to change the proposal content based on the update of the degree-of-affinity data, the degree-of-interest data, and the trip preference data for to the two users with the proposal execution unit…; paragraph 0084, discussing that the trip preference is estimated as an index indicating the degree of preference of the user to take trips based on the data of the burden on the user when the user takes a trip. Further, the trip proposal content is changed in accordance with the trip preference estimated).
The Courtney-Gulati-Kline combination describes features related to transportation services. Suzuki discusses an information providing method for proposing a trip to a user. Therefore, they are deemed to be analogous as they both are directed towards transportation service management systems. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the Courtney-Gulati-Kline combination with Suzuki because the references are analogous art because they are both directed to solutions for transportation services, which falls within applicant’s field of endeavor (system and method for transportation services), and because modifying Courtney-Gulati-Kline combination to include Suzuki’s feature for including modifying the corresponding weight of at least one respective state based on the feedback data, in the manner claimed, would serve the motivation of allowing a trip to be efficiently proposed (Suzuki at paragraph 0111); and further obvious because the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Tan et al., Pub. No.: US 2020/0356909 A1 – describes a method and system for recommending multi-modal itineraries. Further describes that ranking each itinerary in the set of itineraries may include: inputting the rider context information into the machine learning model; scoring each itinerary in the set of itineraries based on a set of results from the machine learning model; and ranking the score of each itinerary in the set of itineraries in descending order.
Mueller et al., Pub. No.: US 2021/0304347 A1 – describes an optimization/planning system that can generate a set of flight plans for a particular aircraft by starting at the beginning of the flight planning period and sequentially generating/adding flight plans for the aircraft until the end of the flight planning period is reached. As one example, at each instance in which the optimization/planning system attempts to generate a new flight plan for an aircraft, the system can generate a plurality of candidate flight plans, score each candidate flight plan according to the aircraft-level objective function, and then select and add the highest scoring flight plan for the aircraft.
Huddleston et al., Pub. No.: US 2005/0159994 A1 – describes that one or more initial plans are generated and evaluated to determine quality scores for the plans. One or more of the plans is selected according to the quality scores and modified to generate modified plans. The modified plans are evaluated to determine updated quality scores for the modified plans. Selection, modification and evaluation of modified plans are repeated until one of the modified plans is satisfactory.
Raduchel et al., Pub. No.: US 2017/0161439 A1 – describes tracking participation and overall health for each employee user. In such a scoring system, positive health behavior can increase the score, while negative health behavior can lower the score.
Rodriguez et al., Patent No.: US 9,953,264 B2 – describes obtaining the user preferences includes obtaining weighting factors to be applied to one or more of the execution time score, the execution cost score, the availability score or the efficiency score, and transforming the information relating to the one or more resources includes aggregating the execution time, the execution cost, the availability score and the efficiency score for each resource as a weighted combination using the weighting factors to provide an overall resource score for each resource, and the transformed information includes the overall resource score for each resource.
Abenoza, Roberto F., Oded Cats, and Yusak O. Susilo. "How does travel satisfaction sum up? An exploratory analysis in decomposing the door-to-door experience for multimodal trips." Transportation 46.5 (2019): 1615-1642 – analyzes data on retrospective evaluations of entire multi-modal trip experiences and satisfaction with individual trip legs.
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/Darlene Garcia-Guerra/
Primary Examiner, Art Unit 3625
Prosecution Insights