DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statement (IDS) filed 12/10/2024 has been received and considered by the examiner. The submission is in compliance with the provisions of 37 CFR 1.97.
Drawings
The drawings are objected to because the specification at paragraph [36] line 3 describes two pick up points 314 and 316 in Fig. 3C; however, Fig. 3C has pick up points 314 and 318, and reference numeral 318 is used again in Fig. 3D. Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Specification
The disclosure is objected to because of the following informalities: Paragraph [38] line 1 says Fig. 3E shows different prices; however, Fig. 3F is the correct figure showing different prices. Paragraph [98] line 4 says the modem is 1416; however, Fig. 8A shows the modem as 1316. Paragraph [101] line 2 says the interconnected bus is 1304; however, Fig. 8A shows the interconnected bus is 1404. Paragraph [132] lines 5 and 6 say the memory is 1004 and the processor is 1002; however, Fig. 11 shows the memory is 804 and the processor is 802.
Appropriate correction is required.
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 1-14 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
In January, 2019 (updated October 2019), the USPTO released new examination guidelines setting forth a two-step inquiry for determining whether a claim is directed to non-statutory subject matter. According to the guidelines, a claim is directed to non-statutory subject matter if:
STEP 1: the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), or
STEP 2: the claim recites a judicial exception, e.g. an abstract idea, without reciting additional elements that amount to significantly more than the judicial exception, as determined using the following analysis:
STEP 2A (PRONG 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon?
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
Using the two-step inquiry, it is clear that claims 1 and 8 are directed toward non-statutory subject matter, as shown below:
STEP 1: Do claims 1 and 8 fall within one of the statutory categories? Yes. The claims are directed toward a method including at least one step and an apparatus.
STEP 2A (PRONG 1): Is the claim directed to a law of nature, a natural phenomenon or an abstract idea? Yes, the claims are directed to an abstract idea.
With regard to STEP 2A (PRONG 1), the guidelines provide three groupings of subject matter that are considered abstract ideas:
Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations;
Certain methods of organizing human activity – fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions); and
Mental processes – concepts that are practicably performed in the human mind (including an observation, evaluation, judgment, opinion).
Claim 1. A method for adaptively identifying an optimal route, comprising:
determining, by a processor, one or more pick up points based on historical data relating to a starting location, the starting location being one that is indicated in a request for a ride from the starting location to a destination location;
determining, by the processor, one or more routes between each of the determined one or more pick up points and the destination location indicated in the ride request;
and adaptively identifying, by the processor, an optimal route from the one or more routes based on at least one of a cheapest route, fastest route, shortest route and shortest walking distance.
The method in claim 1, specifically the limitations emphasized above, is a mental process that can be practicably performed in the human mind and, therefore, an abstract idea. It merely consists of determining one or more pick up points, determining one or more routes, and adaptively identifying an optimal route. This is equivalent to a person mentally deciding pick up points, deciding routes, and determining the optimal route.
Claim 8. A system for adaptively identifying an optimal route, the system comprising: at least one processor;
and at least one memory including computer program code;
the at least one memory and the computer program code configured to, with the at least one processor, cause the system at least to:
determine one or more pick up points based on historical data relating to a starting location, the starting location being one that is indicated in a request for a ride from the starting location to a destination location;
determine one or more routes between each of the determined one or more pick up points and the destination location indicated in the ride request;
and adaptively identify an optimal route from the one or more routes based on at least one of a cheapest route, fastest route, shortest route and shortest walking distance.
The method in claim 8, specifically the limitations emphasized above, is a mental process that can be practicably performed in the human mind and, therefore, an abstract idea. It merely consists of determining one or more pick up points, determining one or more routes, and adaptively identifying an optimal route. This is equivalent to a person mentally deciding pick up points, deciding routes, and determining the optimal route.
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application? No, the claims do not recite additional elements that integrate the judicial exception into a practical application.
With regard to STEP 2A (prong 2), whether the claim recites additional elements that integrate the judicial exception into a practical application, the guidelines provide the following exemplary considerations that are indicative that an additional element (or combination of elements) may have integrated the judicial exception into a practical application:
an additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
an additional element that applies or uses a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition;
an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
While the guidelines further state that the exemplary considerations are not an exhaustive list and that there may be other examples of integrating the exception into a practical application, the guidelines also list examples in which a judicial exception has not been integrated into a practical application:
an additional element merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea;
an additional element adds insignificant extra-solution activity to the judicial exception; and
an additional element does no more than generally link the use of a judicial exception to a particular technological environment or field of use.
In the present case, the additional limitations beyond the above-noted abstract ideas are as follows (where the underlined portions are the “additional limitations” while the bolded portions continue to represent the abstract “idea”).
Claim 1. A method for adaptively identifying an optimal route, comprising:
determining, by a processor, one or more pick up points based on historical data relating to a starting location, the starting location being one that is indicated in a request for a ride from the starting location to a destination location;
determining, by the processor, one or more routes between each of the determined one or more pick up points and the destination location indicated in the ride request;
and adaptively identifying, by the processor, an optimal route from the one or more routes based on at least one of a cheapest route, fastest route, shortest route and shortest walking distance.
Claim 1 does not recite any of the exemplary considerations that are indicative of an abstract idea having been integrated into a practical application. The limitations “by the processor” are claimed generically and are operating in their ordinary capacity such that they do not use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. The processor merely describes how to generally “apply” the otherwise mental judgments in a generic or general purpose computing environment. The processor recited at a high level of generality and merely automates the determining and adaptively identifying steps. These limitations can also be viewed as nothing more than an attempt to generally link the use of the judicial exception to the technological environment of a computer. It should be noted that because the courts have made it clear that mere physicality or tangibility of an additional element or elements is not a relevant consideration in the eligibility analysis, the physical nature of these computer components does not affect this analysis. See MPEP 2106.05(I). Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Claim 8. A system for adaptively identifying an optimal route, the system comprising: at least one processor;
and at least one memory including computer program code;
the at least one memory and the computer program code configured to, with the at least one processor, cause the system at least to:
determine one or more pick up points based on historical data relating to a starting location, the starting location being one that is indicated in a request for a ride from the starting location to a destination location;
determine one or more routes between each of the determined one or more pick up points and the destination location indicated in the ride request;
and adaptively identify an optimal route from the one or more routes based on at least one of a cheapest route, fastest route, shortest route and shortest walking distance.
Claim 8 does not recite any of the exemplary considerations that are indicative of an abstract idea having been integrated into a practical application. The limitations “A system for adaptively identifying an optimal route, the system comprising: at least one processor”, “and at least one memory including computer program code”, and “the at least one memory and the computer program code configured to, with the at least one processor, cause the system at least to” are claimed generically and are operating in their ordinary capacity such that they do not use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. The system comprising at least one processor and memory including computer program code merely describe how to generally “apply” the otherwise mental judgments in a generic or general purpose computing environment. The system comprising at least one processor and memory including computer program code are recited at a high level of generality and merely automate the determining and adaptively identifying steps. These limitations can also be viewed as nothing more than an attempt to generally link the use of the judicial exception to the technological environment of a computer. It should be noted that because the courts have made it clear that mere physicality or tangibility of an additional element or elements is not a relevant consideration in the eligibility analysis, the physical nature of these computer components does not affect this analysis. See MPEP 2106.05(I). Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No, the claims do not recite additional elements that amount to significantly more than the judicial exception.
With regard to STEP 2B, whether the claims recite additional elements that provide significantly more than the recited judicial exception, the guidelines specify that the pre-guideline procedure is still in effect. Specifically, that examiners should continue to consider whether an additional element or combination of elements:
adds a specific limitation or combination of limitations that are not well-understood, routine, conventional activity in the field, which is indicative that an inventive concept may be present; or
simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, which is indicative that an inventive concept may not be present.
Regarding Step 2B of the 2019 PEG, independent claims 1 and 8 do not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claims do not integrate the abstract idea into a practical application.
As discussed above with respect to integration of the abstract idea into a practical application, the additional limitation(s) of “by the processor”, “A system for adaptively identifying an optimal route, the system comprising: at least one processor”, “and at least one memory including computer program code”, and “the at least one memory and the computer program code configured to, with the at least one processor, cause the system at least to” is/are merely means to apply the exception and do not amount to “significantly more”, as adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, e.g., a limitation indicating that a particular function such as creating and maintaining electronic records is performed by a computer, as discussed in Alice Corp., 573 U.S. at 225-26, 110 USPQ2d at 1984, are not sufficient to amount to significantly more than the judicial exception.
Thus, since claims 1 and 8 are: (a) directed toward an abstract idea, (b) do not recite additional elements that integrate the judicial exception into a practical application, and (c) do not recite additional elements that amount to significantly more than the judicial exception, it is clear that claims 1 and 7 are directed towards non-statutory subject matter.
Dependent claims 2-7 and 9-14 further limit the abstract idea without integrating the abstract idea into practical application or adding significantly more.
As such, claims 1-14 are rejected under 35 USC 101 as being drawn to an abstract idea without significantly more, and thus are ineligible.
Claim Rejections - 35 USC § 102
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 (i.e., changing from AIA to pre-AIA ) 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.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-6, 8-13 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Chachra (US 20240337497 A1).
Regarding Claim 1, Chachra teaches A method for adaptively identifying an optimal route, comprising: determining, by a processor, one or more pick up points based on historical data relating to a starting location, the starting location being one that is indicated in a request for a ride from the starting location to a destination location (See at least paragraph [0040], “Similar to FIGS. 2A-2B, in the example 230 of FIG. 2C, there are a number of buildings 214 with roads 216 running between them and the person has requested a ride (e.g., transport) at a location 202 outside one of the buildings, with a similar destination (not shown) indicated in the request...The pickup location score threshold value may be determined based on historical data of previous pickup locations, time to pickup, time from pickup to start of ride, or other factors such as ease of navigation to the location, legality and safety of the location for the provider to pick up the requestor, historical reduced cancelations, historical numbers of successful pickups, etc. Thus a location having a score that meets the pickup location score threshold may indicate that the location is suitable for a pickup and likely to be successful”, paragraph [0041], “Curb segments associated with locations having moderate pickup location scores 240A-240F are shown in a second pattern (e.g., a dotted pattern). The locations or curb segments with moderate pickup location scores may meet a pickup location score threshold but may not be excellent locations for interactions between providers and requestors. The moderate pickup location scores may indicate that some delay and/or contacts between providers and requestors is probably for the matched request but that the delay is minimal or reasonable”, and paragraph [0047], “As shown in FIG. 2C, the dynamic transportation matching system may identify a set of alternate request locations associated with one or more of the curb segments 238A-238M, 240A-240F, and 242A and may identify that a location associated with the curb sub-segment 242A is the best alternate request location for the request. As such, the dynamic transportation matching system may modify the request location 202 to the modified request location 226 and navigate the requestor to the modified request location 226. In this example, the request may travel around the block further than the example shown in FIG. 2B to meet the provider. Once the provider 206 picks up the requestor at the location 226, the provider 206 may continue with the route 222 to the destination (not shown).” The system determines pickup-location scores for locations using historical ride data, and identifies a best alternate request location based on those scores. The system further discloses that a ride is requested at a location with a destination indicated in the request. Accordingly, the system determines one or more pickup points based on historical data relating to a starting location.); determining, by the processor, one or more routes between each of the determined one or more pick up points and the destination location indicated in the ride request (See at least paragraph [0079], “The travel time estimation module 134B may map a plurality of possible routes from the provider location to the request location as well as the alternate request locations and generate an estimated arrival time for each of the potential mapped routes…Accordingly, the travel time estimation module 134B may determine a navigation route associated with the request location and an estimated travel time for each of the providers.”); and adaptively identifying, by the processor, an optimal route from the one or more routes based on at least one of a cheapest route, fastest route, shortest route and shortest walking distance (See at least paragraph [0079], “The travel time estimation module 134B may map a plurality of possible routes from the provider location to the request location as well as the alternate request locations and generate an estimated arrival time for each of the potential mapped routes. The travel time estimation module 134B may select the fastest route and/or the most probable route for each of the providers and the corresponding estimated travel time for that route as the estimated travel time for the provider... Accordingly, the travel time estimation module 134B may determine a navigation route associated with the request location and an estimated travel time for each of the providers. Further, the estimated time may be determined through any suitable method including taking an average of multiple routes, selecting the fastest route, adding additional cushion time when certainty is low for the estimate of the time, etc.” The system selects the fastest route from multiple routes, thereby identifying an optimal route based on at least one of the fastest route.).
Regarding Claim 2, Chachra teaches The method of claim 1, as set forth in the anticipation rejection above. Chachra teaches wherein the historical data indicates a plurality of pick up points and location information for each of the plurality of pick up points, and determining the one or more pick up points further comprises selecting, from the plurality of pick up points, one or more pick up points that are in proximity to the starting location based on the location information (See at least paragraph [0049], “According to an embodiment, a number of alternate request locations 306, such as corresponding to curb segments within a particular area (e.g., within a threshold distance 304 of the request location 302) may be determined. According to an embodiment, a threshold distance 304 from the request location 302 may be determined along with a number of alternate request locations 306 within the threshold distance 304.” The system determines alternate request locations within a threshold distance of a request location, thereby selecting pickup points based on proximity to the starting location.).
With respect to claim 9, please see the rejection above with respect to claim 2, which is commensurate in scope to claim 9, with claim 2 being drawn to a method for adaptively identifying an optimal route and claim 9 being drawn to a corresponding system.
Regarding Claim 3, Chachra teaches The method of claim 1, as set forth in the anticipation rejection above. Chachra teaches wherein determining the one or more routes further comprises calculating a first set of estimated time and distance for walking from the starting location to each of the one or more pick up points, and a second set of estimated time and distance for a ride from each of the one or more pick up points to the destination location (See at least paragraph [0051], “In an embodiment, a number of alternate request locations may be sampled within a range of the requested location and a best or most optimal alternate request location may be determined. For example, there may be a 5 minute ETA for the requestor's current requested location but 2 min ETA for the requestor to walk to an alternate request location around the block”, paragraph [0072], “The pickup evaluation module 134A may calculate a distance from the requested pickup location to the actual pickup location”, and paragraph [0079], “The travel time estimation module 134B may map a plurality of possible routes from the provider location to the request location as well as the alternate request locations and generate an estimated arrival time for each of the potential mapped routes…Accordingly, the travel time estimation module 134B may determine a navigation route associated with the request location and an estimated travel time for each of the providers.” The system estimates walking times from a request location to alternate pickup locations and calculates distances between the request location and the pickup locations, thereby providing a first set of estimated time and distance. The system further determines routes for travel from pickup locations, thereby providing a second set of estimated time and distance.).
With respect to claim 10, please see the rejection above with respect to claim 3, which is commensurate in scope to claim 10, with claim 3 being drawn to a method for adaptively identifying an optimal route and claim 10 being drawn to a corresponding system.
Regarding Claim 4, Chachra teaches The method of claim 3, as set forth in the anticipation rejection above. Chachra teaches wherein the historical data indicates a plurality of drop off points and location information for each of the plurality of drop off points, and determining the one or more routes further comprises: determining one or more drop off points that are in proximity to the destination location based on the location information, determining the one or more routes comprising one or more routes between each of the determined one or more pick up points and each of the one or more determined drop off points (See at least paragraph [0040], “Similar to FIGS. 2A-2B, in the example 230 of FIG. 2C, there are a number of buildings 214 with roads 216 running between them and the person has requested a ride (e.g., transport) at a location 202 outside one of the buildings, with a similar destination (not shown) indicated in the request...The pickup location score threshold value may be determined based on historical data of previous pickup locations, time to pickup, time from pickup to start of ride, or other factors such as ease of navigation to the location, legality and safety of the location for the provider to pick up the requestor, historical reduced cancelations, historical numbers of successful pickups, etc. Thus a location having a score that meets the pickup location score threshold may indicate that the location is suitable for a pickup and likely to be successful”, paragraph [0079], “The travel time estimation module 134B may map a plurality of possible routes from the provider location to the request location as well as the alternate request locations and generate an estimated arrival time for each of the potential mapped routes…Accordingly, the travel time estimation module 134B may determine a navigation route associated with the request location and an estimated travel time for each of the providers”, and paragraph [0100], “In an embodiment, the other requestor may include a destination with their request different from the original requestor's destination. The provider's ETD to the new requestor's destination is determined, along with one or more alternate destination locations to the original requestor's destination. An ETD of the provider to the other requestor's destination from one of the alternate destination locations is determined, and if that ETD is less than the original ETD to the new requestor's original destination, then modified transport information including the alternate destination location is sent to the matched provider. For example, the original requestor is going to location A and the ETD is 5 minutes. The other requestor is going to location B and the ETD, including the travel to location B from location A (because the original requestor is being dropped off first) is 10 minutes. It is determined that location C is within a threshold distance of location A, and that the ETD for the other requestor with location C instead of location A is 7 minutes. If that three minute improvement is within the threshold amount, then location C is used as the dropoff point for the original requestor. In an embodiment, the original requestor's computing device will display mapping data including a navigation route from location C to location A (e.g., a walking route) along with an ETT for the original requestor to travel from location C to location A, and an indication is received of the original requestor's acceptance or denial of the change.” The system discloses one or more alternate destination locations, thereby providing a plurality of drop-off pints with associated location information, and further discloses that a selected drop-off point is within a threshold distance of a destination location, thereby determining one or more drop-off points in proximity to the destination location based on the location information. The system further maps routes and determines a navigation route, thereby determining one or more routes between each of the determined pickup points and drop-off points. As previously discussed, the system utilizes historical data in evaluating locations associated with a ride request.); and calculating the second set of estimated time and distance based on a ride from each of the one or more pick up points to each of the one or more determined drop off points (See at least paragraph [0072], “The pickup evaluation module 134A may calculate a distance from the requested pickup location to the actual pickup location” and paragraph [0079], “The travel time estimation module 134B may map a plurality of possible routes from the provider location to the request location as well as the alternate request locations and generate an estimated arrival time for each of the potential mapped routes…Accordingly, the travel time estimation module 134B may determine a navigation route associated with the request location and an estimated travel time for each of the providers.” The system further determines routes for travel from pickup locations to drop-off points, thereby providing a second set of estimated time and distance.).
With respect to claim 11, please see the rejection above with respect to claim 4, which is commensurate in scope to claim 11, with claim 4 being drawn to a method for adaptively identifying an optimal route and claim 11 being drawn to a corresponding system.
Regarding Claim 5, Chachra teaches The method of claim 3, as set forth in the anticipation rejection above. Chachra teaches wherein identifying an optimal route further comprises identifying a route from the one or more routes with a shortest time or distance as the optimal route based on the first and/or second sets of estimated times and distances (See at least paragraph [0079], “The travel time estimation module 134B may map a plurality of possible routes from the provider location to the request location as well as the alternate request locations and generate an estimated arrival time for each of the potential mapped routes. The travel time estimation module 134B may select the fastest route and/or the most probable route for each of the providers and the corresponding estimated travel time for that route as the estimated travel time for the provider... Accordingly, the travel time estimation module 134B may determine a navigation route associated with the request location and an estimated travel time for each of the providers. Further, the estimated time may be determined through any suitable method including taking an average of multiple routes, selecting the fastest route, adding additional cushion time when certainty is low for the estimate of the time, etc.” The system maps a plurality of possible routes and selects the fastest route, thereby identifying a route from the one or more routes with a shortest time as the optimal route based on estimated travel times.).
With respect to claim 12, please see the rejection above with respect to claim 5, which is commensurate in scope to claim 12, with claim 5 being drawn to a method for adaptively identifying an optimal route and claim 12 being drawn to a corresponding system.
Regarding Claim 6, Chachra teaches The method of claim 4, as set forth in the anticipation rejection above. Chachra teaches wherein determining the one or more routes further comprises calculating a third set of estimated time and distance for walking from each of the one or more drop off points to the destination location, and identifying an optimal route further comprises identifying a route from the one or more routes with a shortest time or distance as the optimal route based on the first, second and/or third sets of estimated times and distances (See at least paragraph [0079], “The travel time estimation module 134B may map a plurality of possible routes from the provider location to the request location as well as the alternate request locations and generate an estimated arrival time for each of the potential mapped routes. The travel time estimation module 134B may select the fastest route and/or the most probable route for each of the providers and the corresponding estimated travel time for that route as the estimated travel time for the provider... Accordingly, the travel time estimation module 134B may determine a navigation route associated with the request location and an estimated travel time for each of the providers. Further, the estimated time may be determined through any suitable method including taking an average of multiple routes, selecting the fastest route, adding additional cushion time when certainty is low for the estimate of the time, etc.” and paragraph [0100], “In an embodiment, the other requestor may include a destination with their request different from the original requestor's destination. The provider's ETD to the new requestor's destination is determined, along with one or more alternate destination locations to the original requestor's destination. An ETD of the provider to the other requestor's destination from one of the alternate destination locations is determined, and if that ETD is less than the original ETD to the new requestor's original destination, then modified transport information including the alternate destination location is sent to the matched provider. For example, the original requestor is going to location A and the ETD is 5 minutes. The other requestor is going to location B and the ETD, including the travel to location B from location A (because the original requestor is being dropped off first) is 10 minutes. It is determined that location C is within a threshold distance of location A, and that the ETD for the other requestor with location C instead of location A is 7 minutes. If that three minute improvement is within the threshold amount, then location C is used as the dropoff point for the original requestor. In an embodiment, the original requestor's computing device will display mapping data including a navigation route from location C to location A (e.g., a walking route) along with an ETT for the original requestor to travel from location C to location A, and an indication is received of the original requestor's acceptance or denial of the change.” The system further provides a walking route from a drop-off point to a destination location along with an estimated travel time, thereby teaching calculating a third set of estimated time and distance for walking from the drop-off point to the destination location. The system also selects the fastest route from a plurality of possible routes, thereby identifying an optimal route based on estimated travel times.).
With respect to claim 13, please see the rejection above with respect to claim 6, which is commensurate in scope to claim 13, with claim 6 being drawn to a method for adaptively identifying an optimal route and claim 13 being drawn to a corresponding system.
Regarding Claim 8, Chachra teaches A system for adaptively identifying an optimal route, the system comprising: at least one processor (See at least paragraph [0137], “FIG. 14 shows an example computer system 1400, in accordance with various embodiments. In various embodiments, computer system 1400 may be used to implement any of the systems, devices, or methods described herein. In some embodiments, computer system 1400 may correspond to any of the various devices described herein, including, but not limited, to mobile devices, tablet computing devices, wearable devices, personal or laptop computers, vehicle-based computing devices, or other devices or systems described herein. As shown in FIG. 14, computer system 1400 can include various subsystems connected by a bus 1402. The subsystems may include an I/O device subsystem 1404, a display device subsystem 1406, and a storage subsystem 1410 including one or more computer readable storage media 1408. The subsystems may also include a memory subsystem 1412, a communication subsystem 1420, and a processing subsystem 1422.”); and at least one memory including computer program code (See at least paragraph [0137], “FIG. 14 shows an example computer system 1400, in accordance with various embodiments. In various embodiments, computer system 1400 may be used to implement any of the systems, devices, or methods described herein. In some embodiments, computer system 1400 may correspond to any of the various devices described herein, including, but not limited, to mobile devices, tablet computing devices, wearable devices, personal or laptop computers, vehicle-based computing devices, or other devices or systems described herein. As shown in FIG. 14, computer system 1400 can include various subsystems connected by a bus 1402. The subsystems may include an I/O device subsystem 1404, a display device subsystem 1406, and a storage subsystem 1410 including one or more computer readable storage media 1408. The subsystems may also include a memory subsystem 1412, a communication subsystem 1420, and a processing subsystem 1422.”); the at least one memory and the computer program code configured to, with the at least one processor, cause the system at least to: determine one or more pick up points based on historical data relating to a starting location, the starting location being one that is indicated in a request for a ride from the starting location to a destination location (See at least paragraph [0040], “Similar to FIGS. 2A-2B, in the example 230 of FIG. 2C, there are a number of buildings 214 with roads 216 running between them and the person has requested a ride (e.g., transport) at a location 202 outside one of the buildings, with a similar destination (not shown) indicated in the request...The pickup location score threshold value may be determined based on historical data of previous pickup locations, time to pickup, time from pickup to start of ride, or other factors such as ease of navigation to the location, legality and safety of the location for the provider to pick up the requestor, historical reduced cancelations, historical numbers of successful pickups, etc. Thus a location having a score that meets the pickup location score threshold may indicate that the location is suitable for a pickup and likely to be successful”, paragraph [0041], “Curb segments associated with locations having moderate pickup location scores 240A-240F are shown in a second pattern (e.g., a dotted pattern). The locations or curb segments with moderate pickup location scores may meet a pickup location score threshold but may not be excellent locations for interactions between providers and requestors. The moderate pickup location scores may indicate that some delay and/or contacts between providers and requestors is probably for the matched request but that the delay is minimal or reasonable”, paragraph [0047], “As shown in FIG. 2C, the dynamic transportation matching system may identify a set of alternate request locations associated with one or more of the curb segments 238A-238M, 240A-240F, and 242A and may identify that a location associated with the curb sub-segment 242A is the best alternate request location for the request. As such, the dynamic transportation matching system may modify the request location 202 to the modified request location 226 and navigate the requestor to the modified request location 226. In this example, the request may travel around the block further than the example shown in FIG. 2B to meet the provider. Once the provider 206 picks up the requestor at the location 226, the provider 206 may continue with the route 222 to the destination (not shown)”, and paragraph [0137], “FIG. 14 shows an example computer system 1400, in accordance with various embodiments. In various embodiments, computer system 1400 may be used to implement any of the systems, devices, or methods described herein. In some embodiments, computer system 1400 may correspond to any of the various devices described herein, including, but not limited, to mobile devices, tablet computing devices, wearable devices, personal or laptop computers, vehicle-based computing devices, or other devices or systems described herein. As shown in FIG. 14, computer system 1400 can include various subsystems connected by a bus 1402. The subsystems may include an I/O device subsystem 1404, a display device subsystem 1406, and a storage subsystem 1410 including one or more computer readable storage media 1408. The subsystems may also include a memory subsystem 1412, a communication subsystem 1420, and a processing subsystem 1422.” The system determines pickup-location scores for locations using historical ride data, and identifies a best alternate request location based on those scores. The system further discloses that a ride is requested at a location with a destination indicated in the request. Accordingly, the system determines one or more pickup points based on historical data relating to a starting location.); determine one or more routes between each of the determined one or more pick up points and the destination location indicated in the ride request (See at least paragraph [0079], “The travel time estimation module 134B may map a plurality of possible routes from the provider location to the request location as well as the alternate request locations and generate an estimated arrival time for each of the potential mapped routes…Accordingly, the travel time estimation module 134B may determine a navigation route associated with the request location and an estimated travel time for each of the providers.”); and adaptively identify an optimal route from the one or more routes based on at least one of a cheapest route, fastest route, shortest route and shortest walking distance (See at least paragraph [0079], “The travel time estimation module 134B may map a plurality of possible routes from the provider location to the request location as well as the alternate request locations and generate an estimated arrival time for each of the potential mapped routes. The travel time estimation module 134B may select the fastest route and/or the most probable route for each of the providers and the corresponding estimated travel time for that route as the estimated travel time for the provider... Accordingly, the travel time estimation module 134B may determine a navigation route associated with the request location and an estimated travel time for each of the providers. Further, the estimated time may be determined through any suitable method including taking an average of multiple routes, selecting the fastest route, adding additional cushion time when certainty is low for the estimate of the time, etc.” The system selects the fastest route from multiple routes, thereby identifying an optimal route based on at least one of the fastest route.).
Claim Rejections - 35 USC § 103
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 (i.e., changing from AIA to pre-AIA ) 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.
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, 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.
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.
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.
Claim(s) 7 and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chachra (US 20240337497 A1) in view of Tolkin (US 20170169535 A1).
Regarding Claim 7, Chachra teaches The method of claim 1, as set forth in the anticipation rejection above. Chachra does not explicitly disclose, however, Tolkin, in the same field of endeavor, teaches wherein determining the one or more routes further comprises calculating an estimated price for a ride from each of the one or more pick up points to the destination location, and identifying an optimal route further comprises identifying a route from the one or more routes with a cheapest price as the optimal route based on the estimated prices (See at least paragraph [0043], “To identify a suggested pickup location for the trip, the eligible pickup locations for are scored 335 for each provider. To score 335 the eligible pickup locations, the pickup location module 145 determines the total cost of travel for each pickup location. The cost of travel for a pickup location is evaluated based on the estimated time to reach the pickup location from the provider's current location (ETA), and the estimated time to reach the destination from the pickup location (ETD). The cost of travel may be determined by the routing module 155. These travel costs may account for the direction of travel of the provider at the time of the request, traffic conditions, and other routing conditions.” The system determines a cost of travel for each pickup location and selects a lowest-cost option, and price represents a cost metric for route selection.).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date to combine the invention of Chachra with the teachings of Tolkin such that the system for determining alternate request locations for a ride request of Chachra is further configured to, wherein determining the one or more routes further comprises calculating an estimated price for a ride from each of the one or more pick up points to the destination location, and identifying an optimal route further comprises identifying a route from the one or more routes with a cheapest price as the optimal route based on the estimated prices, as taught by Tolkin (See paragraph [0043].), with a reasonable expectation of success. The motivation for doing so would be reducing distance and time spent traveling by the provider, reducing the time the client has to wait, and improve the effiency of the network service, as taught by Tolkin (See paragraph [0003].).
With respect to claim 14, please see the rejection above with respect to claim 7, which is commensurate in scope to claim 14, with claim 7 being drawn to a method for adaptively identifying an optimal route and claim 14 being drawn to a corresponding system.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JEWEL ASHLEY KUNTZ whose telephone number is (571)270-5542. The examiner can normally be reached M-F 8:30am-5:30pm.
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/JEWEL A KUNTZ/Examiner, Art Unit 3666
/ANNE MARIE ANTONUCCI/Supervisory Patent Examiner, Art Unit 3666
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