DETAILED ACTION
Notice to Applicant
The following is a FINAL Office action upon examination of application number 18/890,898 filed on 09/20/2024. 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 18/890,898 filed 09/20/2024 is a Continuation of application 17/219,513, filed 03/31/2021. Application 17/219,513 is a Continuation of application 15/412,559, filed 01/23/2017.
Response to Amendment
In the response filed March 16, 2026, Applicant amended claims 1-2, 4-5, 7-12, and 17-20, and did not cancel any claims. No new claims were presented for examination.
Applicant's amendments to claim 10 are hereby acknowledged. The amendments are sufficient to overcome the previously issued claim objection; accordingly, this objection has been removed.
Applicant's amendments to claims 4-5 and 7 are hereby acknowledged. The amendments are sufficient to overcome the previously issued rejection of claims 4-5 and 7-10 under 35 U.S.C. 112(b); accordingly, this rejection has been withdrawn.
Applicant's amendments to claims 1, 11, 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
Applicant's arguments filed March 16, 2026, have been fully considered.
Applicant submits “the Office Action alleges that the claims fall into the "Certain Methods of Organizing Human Activity" abstract idea. Applicant respectfully disagrees.” More specifically, Applicant submits “Regarding the first prong, the Office Action alleges that claim 1 is directed to an abstract idea and falls under the subject matter grouping of "certain methods of organizing a human activity including managing commercial interactions." Office Action at 5. Applicant respectfully disagrees...For example, amended claim 1 recites, "based at least in part on the driving behavior or the determined time of arrival, transmit, over the one or more networks, an instruction to the device, wherein the instruction is used by the device to display information indicative of altering the driving behavior to increase fuel efficiency of the freight vehicle." Such a feature, for example, is certainly not directed to any of the described methods of organizing human activity.” [Applicant’s Remarks, 03/16/2026, pages 7-8, 9]
With particular respect to the §101 rejection of claim 1-20, Applicant first submits that “the claims do not fall into the "Certain Methods of Organizing Human Activity" abstract idea.” The Examiner maintains that the claims plainly set forth or describe steps encompassing managing personal behavior or relationships or interactions, which fall under “certain methods of organizing human activity” abstract idea grouping set forth in MPEP 2106. For example, the steps for receiving request data comprising a location and a time, receiving sensor information and location information indicating a current location of the freight vehicle operating over a portion of a route, determining, based on the sensor information, a driving behavior associated with the freight vehicle over the portion of the route, determining a time of arrival of the freight vehicle to the location, and based at least in part on the driving behavior or the determined time of arrival, transmit an instruction wherein the instruction is used to display information indicative of altering the driving behavior cover embodiments for organizing human activity given that the sequence of activities pertain to monitoring and human behavior and giving instructions to a driver based on the driving behavior, which falls squarely within the realm of “managing personal behavior or relationships or interactions between people,” as explained by the “Certain Methods of Organizing Human Activity” abstract idea groping set forth in MPEP 2106. The claims recites limitation related to monitoring driving behavior and providing an instruction to improve fuel efficiency, which falls into the category of organizing human activity, specifically how a driver should act. The steps are primarily about guiding human behavior rather than improving the operation of the computer or vehicle system itself.
Lastly, in response to Applicant’s argument that “claim 1 recites, "based at least in part on the driving behavior or the determined time of arrival, transmit, over the one or more networks, an instruction to the device, wherein the instruction is used by the device to display information indicative of altering the driving behavior to increase fuel efficiency of the freight vehicle." Such a feature, for example, is certainly not directed to any of the described methods of organizing human activity,” it is noted that this language merely describes using information (i.e., driving behavior and ETA) to make a decision and provide guidance to a human driver. This constitutes evaluating data and providing guidance, which falls within the category of “Certain methods of organizing human activity,” such as managing and influencing driver behavior. Further the claim ultimately results in displaying information to a driver to influence behavior, rather than improving the functioning of the vehicle or the computing system itself.
Accordingly, Applicant’s argument is not persuasive because the claims have been shown to recite an abstract idea via limitations falling under the “Certain methods of organizing human activity” abstract idea groupings set forth in MPEP 2106 via limitations that set forth steps for managing personal behavior or relationships or interactions between people. The Office maintains that the claims recite an abstract idea.
Applicant submits “Even if claim 1 is directed to an abstract idea-which, Applicant submits, it is not-Applicant asserts that the claim recites a combination of additional elements such that the claim as a whole integrates the alleged abstract idea into a practical application. Far from "[t]he recited additional elements are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using generic computer components" as the Office Action asserts, claim 1 "includes specific features that were specifically designed to achieve an improved technological result." For example, claim 1 recites at least, receiving from a device on-board a freight vehicle, sensor information and location information indicating a current location of the freight vehicle operating over a portion of a route," determining "based on the sensor information, a driving behavior associated with the freight vehicle over the portion of the route," and displaying information indicative of "altering the driving behavior to increase fuel efficiency of the freight vehicle." These features integrate the alleged abstract idea into a practical application. Therefore, in addition to the reasons stated above, Applicant respectfully submits that claim 1 is not "directed to" an abstract idea at least because the claim is not eligible under Prong Two of the Step 2A analysis.” [Applicant’s Remarks, 03/16/2026, page 10]
The Examiner respectfully disagrees. In response, it is noted that the additional elements in exemplary claim 1 are: one or more processors, one or more memory resources storing instructions that are executable by the one or more processors, the computing system, over one or more networks, a device on-board a freight vehicle, and one or more sensors of the device, which merely serve to tie the abstract idea to a particular technological environment (computer-based operating environment) via generic computing hardware, software/instructions, which is not sufficient to amount to a practical application, as noted in MPEP 2106.
Furthermore, 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 processors, memory resources, computing system, device, sensors, or technological elements are modified or improved upon in any discernible manner. Instead, the result produced by the claims is simply information indicative of altering the driving behavior of the freight operator which is not a technical result or improvement thereof. Nevertheless, even assuming arguendo that an improvement was achieved, improving the process of providing information to a driver regarding their driving behavior, at most, seems to provide an improvement to a business process using generic computing elements, such that any incidental improvement achieved by automating the claim steps would come from the capabilities of a general-purpose computer rather than the sequence of steps/activities recited in the method itself, which does not materially alter the patent eligibility of the claim. See Bancorp Servs., L.L.C. v. Sun Life Assurance Co. of Can. (U.S.), 687 F.3d 1266, 1278 (Fed. Cir. 2012) (“[T]he fact that the required calculations could be performed more efficiently via a computer does not materially alter the patent eligibility of the claimed subject matter.”) (cited in the Federal Circuit's FairWarning decision).
Furthermore, the additional elements fail to integrate the abstract idea into a practical application because they 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.
Moreover, it is noted that the claim does not recite any specific technological improvement to the vehicle, sensors, or computing system, but instead uses generic components to provide information to a human driver for behavioral modification. For the reasons above, this argument is found unpersuasive.
For the reasons above along with the reasons set forth in the updated §101 rejection set forth below, Applicant’s amendments and arguments concerning the §101 rejection are not sufficient to overcome the rejection.
Applicant submits “None of the cited references teach or suggest at least "determine, based on the sensor information, a driving behavior associated with the freight vehicle over the portion of the route," as recited by independent claim 1.” [Applicant’s Remarks, 03/16/2026, page 12]
In response to the Applicant’s argument that “none of the cited references teach or suggest at least "determine, based on the sensor information, a driving behavior associated with the freight vehicle over the portion of the route," as recited by independent claim 1,” 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.
Applicant submits “While Bednarek mentions "the telematics system may also include or integrate with an event data recorder or EDR installed in the vehicle to record information related to vehicle events." Id. at [0151], the ERD described by Bednarek does not "determine, based on the sensor information, a driving behavior" as recited by the independent claim 1.” [Applicant’s Remarks, 03/16/2026, page 12]
The Examiner respectfully disagrees. With respect to the §103 rejection of independent claim 1, Applicant argues that “Bednarek does not determine, based on the sensor information, a driving behavior." However, in at least paragraphs 0151, 0245, 0246, Bednarek discloses monitoring driver performance, including speed, safety violations, and other operational behaviors, and determining performance based outcomes (i.e., adjusting tips). These citations rely on vehicle sensors or telematics systems to collect data. This teaches analyzing sensor and vehicle data to determine driving behavior, which corresponds to the claimed limitation “determine, based on the sensor information, a driving behavior.” Although Bednarek also describes EDRs (event data recorders) recording raw vehicle events, the system further evaluates this data to determine driver behavior. Thus, given the broadest reasonable interpretation consistent with the specification in construing the claimed invention, it is Examiner’s position that the disclosure of Bednarek teaches the disputed limitation. Accordingly, this argument is found unpersuasive.
Applicant submits “that the EDR system described by Bednark” does not teach “displaying information indicative of "altering the driving behavior to increase fuel efficiency of the freight vehicle”.” [Applicant’s Remarks, 03/16/2026, page 12]
In response to Applicant’s argument that Bednarek does not teach “wherein the instruction is used by the operator device to display information indicative of altering the driving behavior of the freight operator to increase fuel efficiency of the freight vehicle,” the Examiner notes the limitation being argued by Applicant as being newly amended to the claims in the response filed
03/16/2026, which has 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 updated ground of rejection under §103 set forth in the instant Office action, which incorporates new citations to address the amended limitations in claim 1 and supports a conclusion of obviousness of the amended claims. Moreover, it is noted that Bednarek was not asserted as teaching the disputed limitation.
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 Rejections - 35 USC § 101
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.
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 system (claims 1-10), method (claims 11-19), and non-transitory computer-readable medium (claim 20), are directed to at least one potentially eligible category of subject matter (i.e., machine, process, and article of manufacture, 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 managing the driving behavior of a freight operator, which encompasses activity for managing personal behavior or relationships or interactions (e.g., following rules or instructions). With respect to independent claim 1, the limitations reciting the abstract idea are indicated in bold below: one or more processors; and one or more memory resources storing instructions that are executable by the one or more processors to cause the computing system to: receive, over one or more networks, request data comprising a location and a time; receive, over the one or more networks, from a device on-board a freight vehicle, sensor information and location information indicating a current location of the freight vehicle operating over a portion of a route, wherein the sensor information is provided by one or more sensors of the device; determine, based on the sensor information, a driving behavior associated with the freight vehicle over the portion of the route; determine, using the location information, a time of arrival of the freight vehicle to the location; and based at least in part on the driving behavior or the determined time of arrival, transmit, over the one or more networks, an instruction to the device, wherein the instruction is used by the device to display information indicative of altering the driving behavior to increase fuel efficiency of the freight vehicle. These steps are organizing human activity by managing interactions between people by following rules, or instructions. The claim recites limitations that fall under the “Certain Methods of Organizing Human Activity” abstract idea grouping because the limitations involve monitoring a freight operator’s driving behavior, determining arrival times, and providing instruction to the operator to influence the operator’s action, which are abstract processes related to human action coordination.
Therefore, because the limitations above set forth activities falling within the “Certain methods of organizing human activity” 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 11 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: one or more processors, one or more memory resources storing instructions that are executable by the one or more processors, the computing system, over one or more networks, a device on-board a freight vehicle, and one or more sensors of the device (claim 1), over one or more networks, a device on-board a freight vehicle, and one or more sensors of the device (claim 11), a non-transitory computer-readable medium storing instructions that are executable by one or more processors, over one or more networks, a device on-board a freight vehicle, and one or more sensors of the 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 “transmitting” and “display” steps are evaluated as additional elements, these steps amount at most to insignificant extra-solution activity, which is not indicative of a practical application, as noted in 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: one or more processors, one or more memory resources storing instructions that are executable by the one or more processors, the computing system, over one or more networks, a device on-board a freight vehicle, and one or more sensors of the device (claim 1), over one or more networks, a device on-board a freight vehicle, and one or more sensors of the device (claim 11), a non-transitory computer-readable medium storing instructions that are executable by one or more processors, over one or more networks, a device on-board a freight vehicle, and one or more sensors of the 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 [0194]: “The various illustrative steps, components, and computing systems (such as devices, databases, interfaces, and engines) described in connection with the embodiments disclosed herein can be implemented or performed by a machine, such as a general purpose processor, a digital signal processor…”). 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.).
With respect to the “transmitting” and “display” steps, these steps amount to insignificant extra-solution activity, which does not amount to a practical application (MPEP 2106.05(g)), nor add significantly more because such activity 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) - Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network).
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 2-10 and 12-19 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 2-10 recite “wherein the instruction indicative of altering the driving behavior maintains an arrival of the freight vehicle at the location to be at the time,” “wherein the sensor information comprises fuel consumption information of the freight vehicle,” “wherein the sensor information comprises weight information of a freight being carried by the freight vehicle, determine a weight of the freight, wherein the driving behavior is further based on the weight of the freight,” “wherein the sensor information further comprises fuel level information, obtain location information of one or more fuel stops associated with the route; and determine a refueling location for the freight vehicle based on the fuel level information, the location information of one or more fuel stops, and the driving behavior,” “wherein the instruction indicative of altering the driving behavior is associated with a change in an acceleration, a braking, or a speed of the freight vehicle,” “wherein the instructions cause the computing system to: determine a likelihood of executing the request data, based on additional information; and transmit a notification to the device associated with the freight vehicle,” “wherein the request data comprises at least one of: a type of shipment, a size of the shipment, or a weight of the shipment,” “wherein the additional information comprises equipment information,” “wherein determining the likelihood of executing the request data comprises: filtering, one or more freight vehicles that have suitable equipment to execute the request data, based on the equipment information and the additional information,” 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. The other dependent claims have been evaluated as well, but similar to claims 2-10, these claims also recite details of the abstract ideas themselves accompanied by, at most, generic computer implementation, which is not enough to transform the claims into a practical application of the abstract idea or amount to significantly more than the abstract idea itself. Dependent claim 7 recites additional elements of: transmit a shipment invitation to the operator device associated with the freight 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. As noted above, with respect to the “transmitting” step, this step amounts to insignificant extra-solution activity, which does not amount to a practical application (MPEP 2106.05(g)), nor add significantly more because such activity 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) - Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network).
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
17. 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.
18. 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.
19. 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.
20. 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.
21. Claims 1, 3-5, 7-11, 13-15, and 17-20 are rejected under 35 U.S.C. 103 as being unpatentable over Bednarek et al., Pub. No. US 2015/0227890 A1, [hereinafter Bednarek], in view of Mason et al., Pub. No.: US 2016/0334236 A1, [hereinafter Mason].
As per claim 1, Bednarek teaches a computing system (paragraphs 0061, 0142) comprising:
one or more processors (paragraph 0061: “the system preferably includes hardware and software resources including processor(s), Memory(ies), interface(s) and data store(s) for…”; paragraph 0159, discussing that the system include a processing system with one or more high speed Central Processing Unit(s) (CPU), processors, one or more memories and/or other types of computer readable mediums; paragraph 0160); and
one or more memory resources storing instructions that are executable by the one or more processors to cause the computing system (paragraph 0061: “the system preferably includes hardware and software resources including processor(s), Memory(ies), interface(s) and data store(s) for…”; paragraph 0159, discussing that the system include a processing system with one or more high speed Central Processing Unit(s) (CPU), processors, one or more memories and/or other types of computer readable mediums; paragraph 0168, discussing that a number of software components including engines are stored in the memory and are executable by the processor; paragraphs 0147, 0169) to:
receive, over one or more networks, request data comprising a location and a time (paragraph 0220, discussing that the trusted driver query engine is preferably designed such that users (for example, vendors or customers) can request delivery of an order, package or parcel by a trusted driver from a list of trusted drivers stored by the system. Alternatively, the trusted driver query engine of the system can accommodate requests for jobs received from trusted drivers using the system…As shown, the trusted driver query engine initiates at step 900. At step 903, the trusted driver query engine of the system receives a trusted driver delivery request (job request) [i.e., shipment request] and adds the request to the pending deliveries list. At step 905, the trusted driver query engine of the system collects details of the job request including customer information, pickup address, delivery address [i.e., delivery location], maximum time, maximum cost and the user preference as to whether cost or time should take priority. All of this information is added to the newly created job request; paragraph 0222, discussing that optimization engine of the system stores the designated maximum time and maximum cost as the initial values for selected delivery time; paragraph 0240, discussing that the engine receives a new order; paragraph 0227);
receive, over the one or more networks, from a device on-board a freight vehicle, sensor information and location information indicating a current location of the freight vehicle operating over a portion of a route, wherein the sensor information is provided by one or more sensors of the device (paragraph 0220, discussing that the trusted driver query engine of the system retrieves a trusted driver list from memory. The trusted driver query engine of the system then, polls the trusted drivers to obtain availability and location of trusted drivers; paragraph 0222, discussing that the optimization engine of the system retrieves the trusted driver location; paragraph 0227, discussing that the system tracks the trusted driver en route and displays the trusted driver en route location and updates delivery time in real time; paragraph 0230, discussing that a location positioning system is a mechanism for determining the location of an object in space. Well known technologies for this task exist ranging from worldwide coverage with meter accuracy to workspace coverage with sub-millimeter accuracy. The Global Positioning System (GPS) is a space-based satellite navigation system that provides location and time information…; paragraph 0233, discussing that hybrid positioning systems are systems for finding the location of a mobile device using several different positioning technologies. Usually GPS (Global Positioning System) is one major component of such systems, combined with cell tower signals, wireless internet signals, Bluetooth sensors, IP addresses and network environment data, or other local Positioning Systems; paragraph 0151, discussing that the client may be a vehicle telematics device integrated into or otherwise on board an automobile or other vehicle…Telematics are useful in the collection, aggregation, and storage of pertinent data that can be digested locally, or post-processed remotely. Telematics systems typically include GPS based location detection services…The telematics system may also include or integrate with an event data recorder or EDR installed in the vehicle to record information related to vehicle events… Some EDRs continuously record data, overwriting the previous few minutes until a crash stops them, and others are activated by crash-like events (such as sudden changes in velocity) and may continue to record until the accident is over, or until the recording time is expired. EDRs may record a wide range of data elements, potentially including whether the brakes were applied, the speed at the time of impact, the steering angle, and whether seat belt circuits were shown as "Buckled" or "Unbuckled" at the time of the crash);
determine, based on the sensor information, a driving behavior associated with the freight vehicle over the portion of the route (paragraph 0151, discussing that the telematics system may also include or integrate with an event data recorder (EDR) installed in the vehicle to record information related to vehicle events...Some EDRs continuously record data, overwriting the previous few minutes until a crash stops them, and others are activated by crash-like events (such as sudden changes in velocity) and may continue to record until the accident is over, or until the recording time is expired. EDRs may record a wide range of data elements, potentially including whether the brakes were applied, the speed at the time of impact, the steering angle, and whether seat belt circuits were shown as "Buckled" or "Unbuckled" at the time of the crash; paragraph 0245, discussing that a driver safety engine monitors real time driver (courier) speed and safety records. A TIP engine adjusts tips to ensure promptness and safety; paragraph 0246, discussing that the TIP engine determines a performance based TIP based on, for example, speed of delivery, customer satisfaction and, if desired, other factors such as safety and loyalty…The engine monitors the driver through delivery detecting any safety violations or accidents. At step 1637, the engine may adjust the base tip as a result of driving behavior; paragraph 0013);
determine, using the location information, a time of arrival of the freight vehicle to the location (paragraph 0227, discussing that as the driver approaches the delivery location, the logistics engine of the system may notify the customer of the trusted driver's impending arrival at location; paragraph 0347, discussing that when using a central exchange, it is important to synchronize arrival times and departure times); and
transmit, over the one or more networks, an instruction to the device (paragraph 0013, discussing sending pickup and transfer delivery instructions to one of the plurality of couriers; paragraph 0227, discussing that he logistics engine of the system proceeds to finalize job pickup and delivery instructions and transmit the same to the trusted driver; paragraph 0255, discussing generating distinct instructions for each segment of a delivery).
Bednarek, does not explicitly teach based at least in part on the driving behavior or the determined time of arrival, transmit, over the one or more networks, an instruction to the device, wherein the instruction is used by the device to display information indicative of altering the driving behavior to increase fuel efficiency of the freight vehicle. However, Mason in the analogous art of driver routing systems teaches these concepts. Mason teaches:
based at least in part on the driving behavior or the determined time of arrival, transmit, over the one or more networks, an instruction to the device, wherein the instruction is used by the device to display information indicative of altering the driving behavior to increase fuel efficiency of the freight vehicle (paragraph 0008, discussing a system for calculating routes for a vehicle in a vehicle fleet; paragraph 0012, discussing that the routing module may be configured to receive telematics information for a number of vehicles accessing the site over a period of time. The telematics information for each vehicle can be obtained from a number of sensors included in the vehicle; paragraph 0035, discussing that the management devices can be computing devices used by dispatchers, fleet managers, administrators, or other users to manage different aspects of the vehicle management system. For example, a user of a management device can access the vehicle management system to generate routes, dispatch vehicles and drivers,…, and perform other individual vehicle or fleet management functions. With the management devices, users can access and monitor vehicle information obtained from one or more of the in-vehicle devices by the vehicle management system. Such vehicle status information can include data on vehicle routes used, stops, speed, vehicle feature usage, driver behavior and performance, vehicle emissions, vehicle maintenance, energy usage, and the like; paragraph 0065, discussing that the calculated route output module can output the one or more routes identified by the route calculation module. The routes can be output to a vehicle-based display unit, a handheld mobile device, and/or to a remote location over the network…In some embodiments, the calculated route output module can output feedback to a driver (e.g., directions, instructions, warnings, alerts, alarms). For example, the calculated route output module can output a real-time suggested driving route modification based on traffic or weather conditions. The output feedback can include voice commands, audible alerts, and/or on-screen text or graphics. The feedback can advantageously change driver behavior to improve energy efficiency and reduce energy use. In some embodiments, the calculated route output module is in communication with, and controls operation of, a display device and/or one or more audio devices; paragraphs 0034, 0040, 0115).
Bednarek is directed towards a system for coordinating order deliveries in an order distributed distribution system. Mason is directed towards a system for vehicle routing. Therefore they are deemed to be analogous as they both are directed towards vehicle routing 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 Bednarek with Mason because the references are analogous art because they are both directed to solutions for vehicle scheduling and routing, which falls within applicant’s field of endeavor (systems and methods for transportation planning), and because modifying Bednarek to include Mason’s feature for including based at least in part on the driving behavior or the determined time of arrival, transmit, over the one or more networks, an instruction to the device, wherein the instruction is used by the device to display information indicative of altering the driving behavior to increase fuel efficiency of the freight vehicle, in the manner claimed, would serve the motivation of efficiently determining how to route fleet vehicles and changing driver behavior to improve energy efficiency and reduce energy use (Mason, paragraphs 0055, 0065); 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 3, the Bednarek-Mason teaches the computing system of claim 1. Although not explicitly taught by Bednarek, Mason in the analogous art of driver routing systems teaches wherein the sensor information comprises fuel consumption information of the freight vehicle (paragraph 0012, discussing that the routing module may be configured to receive telematics information for a number of vehicles accessing the site over a period of time. The telematics information for each vehicle can be obtained from a number of sensors included in the vehicle. In addition, the routing module can determine an access path based on the telematics information and store the access path at the site details repository for use in routing vehicles to the site; paragraph 0034, discussing that the in-vehicle devices can include computing devices and sensors installed in fleet vehicles. These devices can include navigation functionality, routing functionality, and the like. The in-vehicle devices can receive route information and other information from the vehicle management system. In addition, the in-vehicle devices can report information to the vehicle management system, such as driver location, vehicle sensor data, vehicle status (e.g., maintenance, tire pressure, or the like), vehicle type, cargo, vehicle direction, and so forth; paragraph 0035, discussing that the management devices can be computing devices used by dispatchers, fleet managers, administrators, or other users to manage different aspects of the vehicle management system. For example, a user of a management device can access the vehicle management system to generate routes, dispatch vehicles and drivers, define access paths, select access paths, update site details information for a site, and perform other individual vehicle or fleet management functions. With the management devices, users can access and monitor vehicle information obtained from one or more of the in-vehicle devices by the vehicle management system. Such vehicle status information can include data on vehicle routes used, stops, speed, vehicle feature usage (such as power takeoff device usage), driver behavior and performance, vehicle emissions, vehicle maintenance, energy usage, and the like; paragraph 0053, discussing that the vehicle characteristics module can store vehicle characteristics regarding vehicles in a fleet. These characteristics can be input by a user, for instance. The vehicle characteristics can include, but are not limited to, vehicle energy type based on energy consumption (e.g., gasoline-powered, electric, hybrid, or alternative fuel), vehicle class, vehicle dimensions, vehicle weight, vehicle capacity, vehicle energy functions, maintenance history, and the like; paragraph 0039).
Bednarek is directed towards a system for coordinating order deliveries in an order distributed distribution system. Mason is directed towards a system for vehicle routing. Therefore they are deemed to be analogous as they both are directed towards vehicle routing 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 Bednarek with Mason because the references are analogous art because they are both directed to solutions for vehicle scheduling and routing, which falls within applicant’s field of endeavor (systems and methods for transportation planning), and because modifying Bednarek to include Mason’s feature for including wherein the sensor information comprises fuel consumption information of the freight vehicle, in the manner claimed, would serve the motivation of efficiently determining how to route fleet vehicles and changing driver behavior to improve energy efficiency and reduce energy use (Mason, paragraphs 0055, 0065); 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 4, the Bednarek-Mason teaches the computing system of claim 1. Although not explicitly taught by Bednarek, Mason in the analogous art of driver routing systems teaches wherein the sensor information comprises weight information of a freight being carried by the freight vehicle, and wherein the instruction further cause the computing system to: determine a weight of the freight, wherein the driving behavior is further based on the weight of the freight (paragraph 0006, discussing that the access path is determined automatically based at least in part on context information relating to one or more of the vehicle, cargo carried by the vehicle, and a driver; paragraph 0011, discussing that the site location can include at least one of: a building at the destination site, a loading dock of the building, a refrigerated loading dock of the building, a particular side of the building, a trash location collection at the destination site, a parking location at the destination site, a delivery entrance of the building, a customer entrance of the building, a long-term parking location at the destination site, an overnight parking location at the destination site, a gate, an inner gate within the site, a security station, and a user-specified location at the destination site. In addition, the context information can include at least one of: preferences of the driver, a number of hours the driver has worked, a number of hours the driver is permitted to work over a period of time, a type of the vehicle, an owner of the vehicle, an entity associated with the vehicle fleet, characteristics of cargo carried by the vehicle, characteristics of a job to be performed by the driver, characteristics of the vehicle, a weight of the vehicle, a size of the vehicle...In some cases, the context information is accessed from a number of sensors included in the vehicle; paragraph 0053, discussing that the vehicle characteristics module can store vehicle characteristics regarding vehicles in a fleet. The vehicle characteristics can include, but are not limited to, vehicle energy type based on energy consumption (e.g., gasoline-powered, electric, hybrid, or alternative fuel), vehicle class, vehicle dimensions, vehicle weight (e.g., unloaded or loaded, estimated or actual), vehicle capacity, vehicle energy functions, maintenance history, and the like; paragraph 0104, discussing that the routing module selects an access path at the site based on the context information in the site details information. For example, the context information identifies a vehicle as being a refrigerated truck, access path may be selected that leads to a refrigerated loading dock. However, if the context information identifies the vehicle is carrying dry goods, and access path may be selected that leads to a different loading dock, such as a non-refrigerated loading dock. As another example, if the vehicle is identified as exceeding a particular weight, a different access path may be selected than if the vehicle does not exceed the particular weight).
Bednarek is directed towards a system for coordinating order deliveries in an order distributed distribution system. Mason is directed towards a system for vehicle routing. Therefore they are deemed to be analogous as they both are directed towards vehicle routing 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 Bednarek with Mason because the references are analogous art because they are both directed to solutions for vehicle scheduling and routing, which falls within applicant’s field of endeavor (systems and methods for transportation planning), and because modifying Bednarek to include Mason’s feature for including wherein the sensor information comprises weight information of a freight being carried by the freight vehicle, and wherein the instruction further cause the computing system to: determine a weight of the freight, wherein the driving behavior is further based on the weight of the freight, in the manner claimed, would serve the motivation of efficiently determining how to route fleet vehicles and changing driver behavior to improve energy efficiency and reduce energy use (Mason, paragraphs 0055, 0065); 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 5, the Bednarek-Mason teaches the computing system of claim 1. Although not explicitly taught by Bednarek, Mason in the analogous art of driver routing systems teaches wherein the sensor information further comprises fuel level information, wherein the instruction further cause the computing system to: obtain location information of one or more fuel stops associated with the route (paragraph 0114, discussing that the route may be generated such that the driver is at a particular location when the route ends or when it is time for the driver to take a break. Advantageously, in certain embodiments, by defining the route so that the driver is at a particular location at a particular time, the drivers mealtimes and resting times can be all aligned with when the driver is at an optimal location for taking a meal break or a sleeping break. In other words, the route can be defined so that the driver is near a restaurant when it is time for a meal break or is near a location where it is permissible for the driver to stop the vehicle and sleep, such as at a site the permits drivers to sleep in the parking lot. Further, the route may be defined based on the condition of the vehicle. For example, if an in-vehicle device indicates that the vehicle will need gas at a particular time or needs to stop for maintenance, the route can be calculated such that the vehicle is near a gas station or a repair station at a particular point in time; paragraph 0133, discussing that in FIG. 8A, Joe creates and entry in the fleet data repository 144 for a supermarket site, Countdown Riccarton. This site may include a number of site locations. For example, the supermarket may include outdoor parking, a parking garage, one or more loading docks, a dumpster location, a water filling station, a gas station affiliated with the supermarket, etc.); and
determine a refueling location for the freight vehicle based on the fuel level information, the location information of one or more fuel stops, and the driving behavior (paragraph 0034, discussing that the in-vehicle devices can include computing devices and sensors installed in fleet vehicles. These devices can include navigation functionality, routing functionality, and the like. The in-vehicle devices can receive route information and other information from the vehicle management system. In addition, the in-vehicle devices can report information to the vehicle management system, such as driver location, vehicle sensor data, vehicle status (e.g., maintenance, tire pressure, or the like), vehicle type, cargo, vehicle direction, and so forth; paragraph 0035, discussing that the management devices can be computing devices used by dispatchers, fleet managers, administrators, or other users to manage different aspects of the vehicle management system. For example, a user of a management device can access the vehicle management system to generate routes, dispatch vehicles and drivers, define access paths, select access paths, update site details information for a site, and perform other individual vehicle or fleet management functions. With the management devices, users can access and monitor vehicle information obtained from one or more of the in-vehicle devices by the vehicle management system. Such vehicle status information can include data on vehicle routes used, stops, speed, vehicle feature usage, driver behavior and performance, vehicle emissions, vehicle maintenance, energy usage, and the like; paragraph 0053, discussing that the vehicle characteristics module can store vehicle characteristics regarding vehicles in a fleet. These characteristics can be input by a user, for instance. The vehicle characteristics can include, but are not limited to, vehicle energy type based on energy consumption (e.g., gasoline-powered, electric, hybrid, or alternative fuel), vehicle class, vehicle dimensions, vehicle weight, vehicle capacity, vehicle energy functions, maintenance history, and the like; paragraph 0114, discussing that the route may be generated such that the driver is at a particular location when the route ends or when it is time for the driver to take a break. Advantageously, in certain embodiments, by defining the route so that the driver is at a particular location at a particular time, the drivers mealtimes and resting times can be all aligned with when the driver is at an optimal location for taking a meal break or a sleeping break. In other words, the route can be defined so that the driver is near a restaurant when it is time for a meal break or is near a location where it is permissible for the driver to stop the vehicle and sleep, such as at a site the permits drivers to sleep in the parking lot. Further, the route may be defined based on the condition of the vehicle. For example, if an in-vehicle device indicates that the vehicle will need gas at a particular time or needs to stop for maintenance, the route can be calculated such that the vehicle is near a gas station or a repair station at a particular point in time).
Bednarek is directed towards a system for coordinating order deliveries in an order distributed distribution system. Mason is directed towards a system for vehicle routing. Therefore they are deemed to be analogous as they both are directed towards vehicle routing 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 Bednarek with Mason because the references are analogous art because they are both directed to solutions for vehicle scheduling and routing, which falls within applicant’s field of endeavor (systems and methods for transportation planning), and because modifying Bednarek to include Mason’s features for including wherein the sensor information further comprises fuel level information, wherein the instruction further cause the computing system to: obtain location information of one or more fuel stops associated with the route, and determine a refueling location for the freight vehicle based on the fuel level information, the location information of one or more fuel stops, and the driving behavior, in the manner claimed, would serve the motivation of efficiently determining how to route fleet vehicles and changing driver behavior to improve energy efficiency and reduce energy use (Mason, paragraphs 0055, 0065); 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 7, the Bednarek-Mason teaches the computing system of claim 1. Bednarek further teaches wherein the instruction cause the computing system to: determine a likelihood of executing the request data, based on additional information (paragraph 0220, discussing that the trusted driver query engine is preferably designed such that users can request delivery of an order, package or parcel by a trusted driver...Alternatively, the trusted driver query engine of the system can accommodate requests for jobs received from trusted drivers using the system…As shown, the trusted driver query engine initiates at step 900. At step 903, the trusted driver query engine of the system receives a trusted driver delivery request (job request) and adds the request to the pending deliveries list. At step 905, the trusted driver query engine of the system collects details of the job request including customer information, pickup address, delivery address, maximum time, maximum cost and the user preference as to whether cost or time should take priority. All of this information is added to the newly created job request…At step 920, the trusted driver query engine of the system generates a list of available local trusted drivers…At step 925, the trusted driver query engine of the system determines whether any local trusted drivers are available; paragraph 0227, discussing that the logistics engine of the system uses identifies possible local drivers using stored or dynamically generated location position information. At step 1117, the logistics engine of the system uses a polling engine to poll the local drivers to obtain availability and delivery capacity and equipment available information; paragraph 0238, discussing that when an order is received, the system determines available couriers. A message is broadcast to all couriers identified as potential couriers based on location, profile and availability. Couriers can "opt in" to the selection process on the delivery order. The system then selects and notifies couriers of the selection; paragraph 0186, 0222); and
transmit a notification to the device associated with the freight vehicle (paragraph 0013, discussing sending transfer delivery instructions to one of the plurality of couriers; paragraph 0227, discussing that the logistics engine of the system proceeds to finalize job pickup and delivery instructions and transmit the same to the trusted driver; paragraph 0238, discussing that when an order is received, the system determines available couriers. A message is broadcast to all couriers identified as potential couriers based on location, profile and availability. Couriers can "opt in" to the selection process on the delivery order. The system then selects and notifies couriers of the selection).
As per claim 8, the Bednarek-Mason teaches the computing system of claim 7. Although not explicitly taught by Bednarek, Mason in the analogous art of driver routing systems teaches wherein the request data comprises at least one of: a type of shipment, a size of the shipment, or a weight of the shipment (paragraph 0034, discussing that one or more in-vehicle devices and management devices communicate with the vehicle management system over a network. The in-vehicle devices can include computing devices and sensors installed in fleet vehicles. These devices an include navigation functionality, routing functionality, and the like. The in-vehicle devices can receive route information and other information from the vehicle management system. In addition, the in-vehicle devices can report information to the vehicle management system, such as driver location, vehicle sensor data, vehicle status (e.g., maintenance, tire pressure, or the like), vehicle type, cargo, vehicle direction, and so forth; paragraph 0053, discussing that the vehicle characteristics module can store vehicle characteristics regarding vehicles in a fleet. These characteristics can be input by a user, for instance. The vehicle characteristics can include, but are not limited to, vehicle energy type based on energy consumption, vehicle class (e.g., passenger vehicle, commercial truck or trailer, bus), vehicle dimensions, vehicle weight (e.g., unloaded or loaded, estimated or actual), vehicle capacity, vehicle energy functions, maintenance history, and the like; paragraph 0079, discussing that the route may be calculated based at least in part on time, distance, use or lack of use of highways, use or lack of use of toll roads, international borders, vehicle size, vehicle cargo, or any other information that may impact the selection or calculation of a route; paragraph 0102, discussing that some examples of context information that may be used for defining or selecting an access path include the following: a type of vehicle, a size of the vehicle, weight of the vehicle,…, cargo carried by the vehicle, a purpose for visiting the site, an expected length of time the driver is to remain at the site, additional sites to be included in the route, the amount of time the driver is driving within a time period, the amount of time the driver is working (e.g., driving, loading or unloading cargo, etc.), a skill of the driver, a time of day, and a set of traffic patterns, etc.; paragraph 0112, discussing that the portion may include the start of the access path, the end of the access path, or an extension of the access path. Further, the portion of the access path may be inferred based at least in part on a number of factors including: another portion of the access path that the vehicle travelled or that has been identified by the routing module 200; context information associated with the vehicle (e.g., vehicle type, cargo type, an entity associated with the vehicle, etc.); paragraph 0115).
Bednarek is directed towards a system for coordinating order deliveries in an order distributed distribution system. Mason is directed towards a system for vehicle routing. Therefore they are deemed to be analogous as they both are directed towards vehicle routing 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 Bednarek with Mason because the references are analogous art because they are both directed to solutions for vehicle scheduling and routing, which falls within applicant’s field of endeavor (systems and methods for transportation planning), and because modifying Bednarek to include Mason’s feature for including wherein the request data comprises at least one of: a type of shipment, a size of the shipment, or a weight of the shipment, in the manner claimed, would serve the motivation of efficiently determining how to route fleet vehicles and changing driver behavior to improve energy efficiency and reduce energy use (Mason, paragraphs 0055, 0065); 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 Bednarek-Mason teaches the computing system of claim 8. Bednarek further teaches wherein the additional information comprises equipment information (paragraph 0224, discussing that another way to address the issue of perishable items is the enlist one or more trusted drivers that have vehicles equipped with refrigeration or warming devices to keep the products at or near the intended temperature thus extending maximum delivery times. In such instances, the availability of such equipment will be stored in the trusted driver profile and used by the logistics system as a factor in allocating deliveries; paragraph 0225, discussing that the system includes a pending deliveries list. Using information on this list, the trusted drive or logistics engine of the system may alert drivers to the impending unfilled delivery orders. The trusted driver could respond with a message indicating the driver's delivery capacity and any special equipment such as refrigeration equipment or warming equipment to keep food or other items cool or warm; paragraph 0227, discussing that the logistics engine of the system uses a polling engine to poll the local drivers to obtain availability and delivery capacity and equipment available information).
As per claim 10, the Bednarek-Mason teaches the computing system of claim 9. Bednarek further teaches wherein determining the likelihood of executing the request data comprises: filtering, one or more freight vehicles that have suitable equipment to execute the request data, based on the equipment information and the additional information (paragraph 0224, discussing that another way to address the issue of perishable items is the enlist one or more trusted drivers that have vehicles equipped with refrigeration or warming devices to keep the products at or near the intended temperature thus extending maximum delivery times. In such instances, the availability of such equipment will be stored in the trusted driver profile and used by the logistics system as a factor in allocating deliveries; paragraph 0225, discussing that the system includes a pending deliveries list. Using information on this list, the trusted drive or logistics engine of the system may alert drivers to the impending unfilled delivery orders. The trusted driver could respond with a message indicating the driver's delivery capacity and any special equipment such as refrigeration equipment or warming equipment to keep food or other items cool or warm; paragraph 0227, discussing that the logistics engine of the system uses a polling engine to poll the local drivers to obtain availability and delivery capacity and equipment available information. At step 1120, the logistics engine of the system places the highest priority order using the trusted driver engine. At step 1123, the logistics engine of the system determines whether the driver can accommodate additional orders. If yes, the logistics engine of the system proceeds to step 1125 and determines whether there are any pending orders in the same vicinity en route for the driver's upcoming delivery order. If yes, the logistics engine of the system determines whether the driver can accommodate that specific order. If yes, the logistics engine of the system places the additional order with the trusted driver at step 1130. The logistics engine of the system then proceeds back to step 1123 and repeats the process until a determination is made that either the driver cannot accommodate any additional orders or that there are no pending orders in the same vicinity or en route. In these instances, the logistics engine of the system proceeds to step 1133 and proceeds to finalize job pickup and delivery instructions and transmit the same to the trusted driver.).
Claim 11 recites substantially similar limitations that stand rejected via the art citations and
rationale applied to claim 1, as discussed above. Further, as per claim 11, the Bednarek-Mason teaches a computer-implemented method (Bednarek, paragraph 0061: “To implement the methods of the present invention, the system preferably includes hardware and software resources including processor(s), Memory(ies), interface(s) and data store(s) for performing…”; paragraph 0141: “Various infrastructures may be used to implement the communication system and method of the present invention.”).
Claim 13 recites substantially similar limitations that stand rejected via the art citations and
rationale applied to claim 3, as discussed above.
Claim 14 recites substantially similar limitations that stand rejected via the art citations and
rationale applied to claim 4, as discussed above.
Claim 15 recites substantially similar limitations that stand rejected via the art citations and
rationale applied to claim 5, as discussed above.
Claim 17 recites substantially similar limitations that stand rejected via the art citations and
rationale applied to claim 7, as discussed above.
Claim 18 recites substantially similar limitations that stand rejected via the art citations and
rationale applied to claim 8, as discussed above.
Claim 19 recites substantially similar limitations that stand rejected via the art citations and
rationale applied to claim 9, as discussed above.
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 Bednarek-Mason teaches a non-transitory computer-readable medium storing instructions that are executable by one or more processors to perform operations (Bednarek, paragraph 0061: “the system preferably includes hardware and software resources including processor(s), Memory(ies), interface(s) and data store(s) for…”; paragraph 0159, discussing that the system include a processing system with one or more high speed Central Processing Unit(s) (CPU), processors, one or more memories and/or other types of computer readable mediums; paragraph 0168, discussing that a number of software components including engines are stored in the memory and are executable by the processor; paragraphs 0147, 0169).
22. Claims 2, 6, 12, and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Bednarek in view of Mason, in further view of Sharma et al., Pub. No.: US 2018/0037241 A1, [hereinafter Sharma].
As per claim 2, the Bednarek-Mason combination teaches the computing system of claim 1. The Bednarek-Mason combination does not explicitly teach wherein the instruction indicative of altering the driving behavior maintains an arrival of the freight vehicle at the location to be at the time. However, Sharma in the analogous art of vehicle monitoring system teaches this concept. Sharma teaches:
wherein the instruction indicative of altering the driving behavior maintains an arrival of the freight vehicle at the location to be at the time (paragraph 0002, discussing that some known vehicle systems may travel according to a trip plan that provides instructions for the vehicle system to implement during movement of the vehicle system so that the vehicle system meets or achieves certain objectives during the trip. For example, the trip plan may dictate throttle settings or brake settings of the vehicle system as a function of time, location, and/or other parameters. The objectives for the trip may include reaching the arrival location at or before a predefined arrival time, increasing fuel efficiency (relative to the fuel efficiency of the vehicle system traveling without following the trip plan), abiding by speed limits and emissions limits, and the like; paragraph 0037, discussing that the trip plan is configured to achieve or increase specific goals or objectives during the trip of the vehicle system, while meeting or abiding by designated constraints, restrictions, and limitations. Some possible objectives include increasing energy (e.g., fuel) efficiency, reducing emissions generation, reducing trip duration, increasing fine motor control, reducing wheel and route wear, and the like. The constraints or limitations include speed limits, schedules (such as arrival times at various designated locations), environmental regulations, standards, and the like. The operational settings of the trip plan are configured to increase the level of attainment of the specified objectives relative to the vehicle system traveling along the route for the trip according to operational settings that differ from the one or more operational settings of the trip plan. One example of an objective of the trip plan is to increase fuel efficiency (e.g., by reducing fuel consumption) during the trip…).
The Bednarek-Mason combination describes features related to transportation planning. Sharma is directed towards a method for generating a trip plan that dictates operational settings to be implemented by a vehicle system moving along a route. Therefore they are deemed to be analogous as they both are directed towards vehicle routing 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 Bednarek-Mason combination with Sharma because the references are analogous art because they are both directed to solutions for vehicle scheduling and routing, which falls within applicant’s field of endeavor (systems and methods for transportation planning), and because modifying the Bednarek-Mason combination to include Sharma’s feature for including wherein the instruction indicative of altering the driving behavior maintains an arrival of the freight vehicle at the location to be at the time, in the manner claimed, would serve the motivation of increasing fuel efficiency relative to the fuel efficiency of the vehicle system traveling without following the trip plan (Sharma, 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 6, the Bednarek-Mason teaches the computing system of claim 1. While Bednarek describes speed sensors (paragraph 0152), the Bednarek-Mason combination does not explicitly teach wherein the instruction indicative of altering the driving behavior is associated with a change in an acceleration, a braking, or a speed of the freight vehicle. However, Sharma in the analogous art of vehicle monitoring system teaches this concept. Sharma teaches:
wherein the instruction indicative of altering the driving behavior is associated with a change in an acceleration, a braking, or a speed of the freight vehicle (paragraph 0002, discussing that some known vehicle systems may travel according to a trip plan that provides instructions for the vehicle system to implement during movement of the vehicle system so that the vehicle system meets or achieves certain objectives during the trip. For example, the trip plan may dictate throttle settings or brake settings of the vehicle system as a function of time, location, and/or other parameters; paragraph 0005, discussing generating a new trip plan in which the vehicle system exceeds the maximum speed through the restricted segment, or modifying the operational settings of the trip plan such that the vehicle system exceeds the maximum speed through the restricted segment; paragraph 0063, discussing that the vehicle system may modify the operational settings of the trip plan such that the vehicle system exceeds the maximum speed through the restricted segment. In such embodiments, the step of modifying the operational settings may occur prior to or as a new trip plan is generated. The step of modifying may include increasing the vehicle speed to a vehicle speed that is equal to or less than the speed limit when the temporary work order is not applied. For example, if the vehicle speed limit is 60 kph when the temporary work order is not applied, but 30 kph when the temporary work order is applied, the vehicle system may increase the vehicle speed from 30 kph to 60 kph after determining that the temporary work order has expired. The vehicle system may generate a new trip plan as the vehicle system increases the vehicle speed or after the vehicle system increases the vehicle speed; paragraph 0087, discussing that upon receiving confirmation from the operator, the operational settings are modified to increase the vehicle speed. As the vehicle speed is increased, a new trip plan may be generated. As another example, after determining that the temporary work order has expired, the operational settings may be automatically modified to increase the vehicle speed. As the vehicle speed is increased, a new trip plan may be generated).
The Bednarek-Mason combination describes features related to transportation planning. Sharma is directed towards a method for generating a trip plan that dictates operational settings to be implemented by a vehicle system moving along a route. Therefore they are deemed to be analogous as they both are directed towards vehicle routing 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 Bednarek-Mason combination with Sharma because the references are analogous art because they are both directed to solutions for vehicle scheduling and routing, which falls within applicant’s field of endeavor (systems and methods for transportation planning), and because modifying the Bednarek-Mason combination to include Sharma’s feature for including wherein the instruction indicative of altering the driving behavior is associated with a change in an acceleration, a braking, or a speed of the freight vehicle, in the manner claimed, would serve the motivation of increasing fuel efficiency relative to the fuel efficiency of the vehicle system traveling without following the trip plan (Sharma, 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.
Claim 12 recites substantially similar limitations that stand rejected via the art citations and
rationale applied to claim 2, as discussed above.
Claim 16 recites substantially similar limitations that stand rejected via the art citations and
rationale applied to claim 6, as discussed above.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Singhal et al., Pub. No.: US 2018/0143639 A1 – describes a vehicle control system that may autonomously make changes to a driving operation of the vehicle.
Hunt et al., Pub. No.: US 2016/0244067 A1 – describes that data is collected during the operation of a vehicle and used to produce a ranking of a driver's performance, and that ranking is shared on a hosted website, such that the drivers can compare their performance metrics to their peers.
Cao, Pub. No.: US 2016/0364812 A1 – describes systems and methods for on-demand transportation.
Sivaraman, Sayanan, and Mohan Manubhai Trivedi. "Looking at vehicles on the road: A survey of vision-based vehicle detection, tracking, and behavior analysis." IEEE transactions on intelligent transportation systems 14.4 (2013): 1773-1795 – provides a review of the literature in on-road vision-based vehicle detection, tracking, and behavior understanding.
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/Darlene Garcia-Guerra/
Primary Examiner, Art Unit 3625
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