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 .
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.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 11/13/2025 has been entered.
Examiner Notes
(1) In the case of amending the Claimed invention, Applicant is respectfully requested to indicate the portion(s) of the specification which dictate(s) the structure relied on for proper interpretation and also to verify and ascertain the metes and bounds of the claimed invention. This will assist in expediting compact prosecution. MPEP 714.02 recites: “Applicant should also specifically point out the support for any amendments made to the disclosure. See MPEP § 2163.06. An amendment which does not comply with the provisions of 37 CFR 1.121 (b), (c), (d), and (h) may be held not fully responsive. See MPEP § 714.” Amendments not pointing to specific support in the disclosure may be deemed as not complying with provisions of 37 C.F.R. 1.131 (b), (c), (d), and (h) and therefore held not fully responsive. Generic statements such as "Applicants believe no new matter has been introduced" may be deemed insufficient.
(2) Examiner cites particular columns, paragraphs, figures and line numbers in the references as applied to the claims below for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the applicant fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the Examiner.
Remarks
Receipt of Applicant’s Amendment file on 11/13/2025 is acknowledged.
Response to Arguments
Applicant’s arguments with respect to claims 1, 10 and 17 have been considered but are moot in view of the new ground(s) of rejection (See new references of LU).
Applicant's arguments filed 11/13/2025 have been fully considered but they are not persuasive.
Applicant argues that the combination of Crapis and LU do not teach ““monitoring movement of the provider device to a first region,” “determining an accumulating regional metric...for the provider device corresponding to an accumulating metric pin of the first region,” “monitoring movement of the provider device from the first region to a second region different from the first region that does not overlap with the first region,” (emphasis added) and located in the second region, providing a transportation match notification to the provider device that comprises the accumulating regional metric”” (page 15, last paragraph, page 16, 1st and 2nd paragraph). Respectfully, it is noted that Crapis and LU teaches:
monitoring movement of the provider device to a first region of the plurality of regions (Crapis, paragraph [0045], as the provider moves, the mapping interface portion updates the location of the provider….; also see Fig. 14, paragraph [0306], determining the transportation provider has moved into the first zone; the act includes monitoring movements of the transportation provider with respect to the geocoded areas within the geocoded region while LU, Fig. 1 of page 5, and Fig. 2 of page 8, page 7, recording the state (open, en-route, on-trip, or offline) at minute t+1, and if he is open, en-route or on-trip we record his location; for drivers that are open at minute t+1, we determine whether each driver remains in the same hexagon I (indicating this lack of motion by j=0), has moved to one of the 6 immediate adjacent hexagons, or has moved to some other hexagon);
determining an accumulating regional metric of the plurality of accumulating regional metrics for the provider device corresponding to an accumulating metric pin of the first region (Crapis, Figs. 13A-13E and 14, paragraph [0307], based on determining that the transportation provider has moved into the first zone, the customized user interface to update the accumulation metric based on an amount of time the transportation provider stay in the first zone while LU, page 7, Fig. 2 of page 8, recording hist state (open, en-route, on-trip, or offline) at minute t+1, and if he is open, en-route or on-trip we record his location; for drivers that are open at minute t+1, we determine whether each driver remains in the same hexagon i (indicating this lack of motion by j=0), has moved to one of the 6 immediate adjacent hexagons, or has moved to some other hexagon; As figure 2 illustrates the driver moving from blue 1.7x would attain extra by moving to 1.9x (2.02x); noted, Crapis indicted that as driver move to first zone, the accumulation metric is displayed with the bonus the driver would have been received; in combination with the indication of user in blue hexagon would attained 1.7x surge price multiplier [incentive including bonus] taught by LU, it reads on as claimed);
monitoring movement of the provider device from the first region to a second region different from the first region that does not overlap with the first region (LU, page 7, Fig. 2 of page 8, recording hist state (open, en-route, on-trip, or offline) at minute t+1, and if he is open, en-route or on-trip we record his location; for drivers that are open at minute t+1, we determine whether each driver remains in the same hexagon i (indicating this lack of motion by j=0), has moved to one of the 6 immediate adjacent hexagons, or has moved to some other hexagon; As figure 2 illustrates the driver moving from blue 1.7x would attain extra by moving to 1.9x (2.02x); noted, monitoring drivers movement by recording his location; determining whether the drivers has moved to one of the 6 immediate adjacent hexagons, wherein as Fig. 2 illustrates these region/hexagon is not overlap, which is an indication of a second region/hexagon is not overlap with the first region/hexagon); and
based on generating a transportation match between the provider device and a requester device located in the second region, providing a transportation match notification to the provider device that comprises the accumulating regional metric (Crapis, paragraph [0045], as the provider moves, the mapping interface portion updates the location of the provider….; also see paragraph [0239]-[0240], identifying each of the capable providers within the target area dispatch radius that is capable of fulfilling a transportation request in the target area during the future time interval; each of capable providers is labeled with probability that the provider will travel to the target area to fulfill a transportation request; also see paragraph [0217], predict an offered incentive that corresponds to the predicted probability; the incentive is represented to a provider as an incremental accumulation metric, which increment as the provider travels toward the target area; also see Figs. 13A-13E and 14, paragraph [0307], determining that the current location of the transportation provider is within the second zone, and updating the accumulation interface portion to include the second color or the second pattern in association with the incremental accumulation metric; noted, as an indication of transportation provider; Fig. 13E-F illustrates the accumulative metrics that the driver would attain when the driver is in the hottest area; also see paragraph [0290], the transportation matching system updates the incentive instructions indicating to the provider that they have entered into the zone; also see paragraph [0301], upon initiating or completing the transportation request, the incremental metric can be awarded to the provider as a bonus; noted, matching the provider with the request when they have entered to the zone corresponding to the incremental metric; upon the initiating or completing the transportation request, awarding the provider with the incremental metric as bonus, which reads on as claimed).
Therefore, the references discloses the limitations.
The rejection of claims 10 and 17 are maintained for similar reasons.
Claim Rejections - 35 USC § 103
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.
Claims 1-5, 7, 9-13 and 15-20 are rejected under 35 U.S.C. 103 as being unpatentable over Crapis et al. (U.S. Pub. 2020/0082315 A1) in view of LU et al. (“Surge pricing Moves Uber’s Driver-Partner”; School of Operations Research and Information Engineering, Cornell University; May 17, 2018).
Regarding claim 1, Crapis teaches: a method comprising:
providing, for display via an interface of a provider device, an accumulating regional metric map displaying a plurality of regions and a plurality of accumulating metric pins corresponding to the plurality of regions (paragraph [0044], generating customized provider interface that includes a mapping interface portion and an accumulation interface portion; the mapping interface includes a map of the target area as well as the current location of the provider; the map portion includes one or more zones that center a target area; the accumulation interface portion includes an incremental bonus metric that increases as the provider approaches the target area and/or based on the time that the provider stays in each of the zones; also see fig. 4A-4B, as shown in Fig. 4A, each of the area in the region includes a forecast of provider 404 and transportation requests…; also see paragraph [0237], the map includes a target areas 1002 (i.e., Area D3); the transportation matching system identifies the target area 1002 based on the generated transportation flow matrix; the transportation flow matrix 722 in Fig. 7C shows Area D2 as having allocation metric of “3”, which means that the target area 1002 is anticipated to have a provider shortage of three providers; also see paragraph [0271], Fig. 12-13).
Crapis does not explicitly disclose: the plurality of accumulating metric pins comprising values of a plurality of accumulating regional metrics that the provider device can attain by entering the plurality of regions.
LU teaches: the plurality of accumulating metric pins comprising values of a plurality of accumulating regional metrics that the provider device can attain by entering the plurality of regions (page 4 and 7, Fig. 1 of page 5, and Fig. 2 of page 8, illustrates the surge heatmap values for the provider device can attain by entering the plurality region; for example, in Fig. 2, by moving from blue hexagon [1.7x] to 1.x, the value would attain by gaining from 1.69x to 2.02x; the driver would prefer to be in hexagons with high surge multipliers, which results in a large payment to the driver; Specifically, Fig. 2 shown multiple options with prices for the users to make choices of moving/repositioning between the origin hexagon and other hexagons; noted, showing of surge prices [interpreted as “values of a plurality of accumulating regional metrics”] corresponding for each hexagon for plurality of hexagon as provider move to the hexagon [interpreted as “the provider device can attain by entering the plurality of regions”]).
It would have been obvious to one of ordinary skill in art before the effective filing date of the claim invention to include the plurality of accumulating metric pins comprising values of a plurality of accumulating regional metrics that the provider device can attain by entering the plurality of regions into zones division of Crapis.
Motivation to do so would be to include the plurality of accumulating metric pins comprising values of a plurality of accumulating regional metrics that the provider device can attain by entering the plurality of regions for reducing spatial search frictions in the ride-sharing market, better aligning drivers’ locations with riders’ desire to take trips (LU, page 2, last paragraph).
Crapis as modified by LU further teach:
monitoring movement of the provider device to a first region of the plurality of regions (Crapis, paragraph [0045], as the provider moves, the mapping interface portion updates the location of the provider….; also see Fig. 14, paragraph [0306], determining the transportation provider has moved into the first zone; the act includes monitoring movements of the transportation provider with respect to the geocoded areas within the geocoded region while LU, Fig. 1 of page 5, and Fig. 2 of page 8, page 7, recording the state (open, en-route, on-trip, or offline) at minute t+1, and if he is open, en-route or on-trip we record his location; for drivers that are open at minute t+1, we determine whether each driver remains in the same hexagon I (indicating this lack of motion by j=0), has moved to one of the 6 immediate adjacent hexagons, or has moved to some other hexagon);
determining an accumulating regional metric of the plurality of accumulating regional metrics for the provider device corresponding to an accumulating metric pin of the first region (Crapis, Figs. 13A-13E and 14, paragraph [0307], based on determining that the transportation provider has moved into the first zone, the customized user interface to update the accumulation metric based on an amount of time the transportation provider stay in the first zone while LU, page 7, Fig. 2 of page 8, recording hist state (open, en-route, on-trip, or offline) at minute t+1, and if he is open, en-route or on-trip we record his location; for drivers that are open at minute t+1, we determine whether each driver remains in the same hexagon i (indicating this lack of motion by j=0), has moved to one of the 6 immediate adjacent hexagons, or has moved to some other hexagon; As figure 2 illustrates the driver moving from blue 1.7x would attain extra by moving to 1.9x (2.02x); noted, Crapis indicted that as driver move to first zone, the accumulation metric is displayed with the bonus the driver would have been received; in combination with the indication of user in blue hexagon would attained 1.7x surge price multiplier [incentive including bonus] taught by LU, it reads on as claimed);
monitoring movement of the provider device from the first region to a second region different from the first region that does not overlap with the first region (LU, page 7, Fig. 2 of page 8, recording hist state (open, en-route, on-trip, or offline) at minute t+1, and if he is open, en-route or on-trip we record his location; for drivers that are open at minute t+1, we determine whether each driver remains in the same hexagon i (indicating this lack of motion by j=0), has moved to one of the 6 immediate adjacent hexagons, or has moved to some other hexagon; As figure 2 illustrates the driver moving from blue 1.7x would attain extra by moving to 1.9x (2.02x); noted, monitoring drivers movement by recording his location; determining whether the drivers has moved to one of the 6 immediate adjacent hexagons, wherein as Fig. 2 illustrates these region/hexagon is not overlap, which is an indication of a second region/hexagon is not overlap with the first region/hexagon); and
based on generating a transportation match between the provider device and a requester device located in the second region, providing a transportation match notification to the provider device that comprises the accumulating regional metric (Crapis, paragraph [0045], as the provider moves, the mapping interface portion updates the location of the provider….; also see paragraph [0239]-[0240], identifying each of the capable providers within the target area dispatch radius that is capable of fulfilling a transportation request in the target area during the future time interval; each of capable providers is labeled with probability that the provider will travel to the target area to fulfill a transportation request; also see paragraph [0217], predict an offered incentive that corresponds to the predicted probability; the incentive is represented to a provider as an incremental accumulation metric, which increment as the provider travels toward the target area; also see Figs. 13A-13E and 14, paragraph [0307], determining that the current location of the transportation provider is within the second zone, and updating the accumulation interface portion to include the second color or the second pattern in association with the incremental accumulation metric; noted, as an indication of transportation provider; Fig. 13E-F illustrates the accumulative metrics that the driver would attain when the driver is in the hottest area; also see paragraph [0290], the transportation matching system updates the incentive instructions indicating to the provider that they have entered into the zone; also see paragraph [0301], upon initiating or completing the transportation request, the incremental metric can be awarded to the provider as a bonus; noted, matching the provider with the request when they have entered to the zone corresponding to the incremental metric; upon the initiating or completing the transportation request, awarding the provider with the incremental metric as bonus, which reads on as claimed).
Regarding claim 2, Crapis as modified by LU teach all claimed limitations as set forth in rejection of claim 1, further teach determining a plurality of transportation requests and corresponding locations of the plurality of transportation requests across the plurality of regions for a time period (Crapis, paragraph [0083], identifying forecasts of providers and transportation requests for a geocoded region… for the time interval; also see paragraph [0237], the map includes a target areas 1002 (i.e., Area D3); the transportation matching system identifies the target area 1002 based on the generated transportation flow matrix; the transportation flow matrix 722 in Fig. 7C shows Area D2 as having allocation metric of “3”, which means that the target area 1002 is anticipated to have a provider shortage of three providers; also see also see fig. 4A-4B, as shown in Fig. 4A, each of the area in the region includes a forecast of provider 404 and transportation requests…); generating cumulative events metrics for the plurality of regions during the time period based on the plurality of transportation requests and the corresponding locations of the plurality of transportation requests relative to the plurality of regions (Crapis, paragraph [0237], the map includes a target areas 1002 (i.e., Area D3); the transportation matching system identifies the target area 1002 based on the generated transportation flow matrix; the transportation flow matrix 722 in Fig. 7C shows Area D2 as having allocation metric of “3”, which means that the target area 1002 is anticipated to have a provider shortage of three providers; also see also see fig. 4A-4B, as shown in Fig. 4A, each of the area in the region includes a forecast of provider 404 and transportation requests…; in combination with Fig. 2, page 8 of LU, it teaches as claimed); and determining the accumulating regional metric for the provider device based on the cumulative events metrics for the plurality of regions (Crapis, paragraph [0239]-[0240], identifying each of the capable providers within the target area dispatch radius that is capable of fulfilling a transportation request in the target area during the future time interval; each of capable providers is labeled with probability that the provider will travel to the target area to fulfill a transportation request; also see paragraph [0200], after one or more providers are selected for an area, or after provider are selected for all target areas, the transportation matching system can send relocating requests to each of the selected drivers; also see paragraph [0217], predict an offered incentive that corresponds to the predicted probability; the incentive is represented to a provider as an incremental accumulation metric, which increment as the provider travels toward the target area).
Regarding claim 3, Crapis as modified by LU teach all claimed limitations as set forth in rejection of claim 2, further teach wherein generating the cumulative events metrics for the plurality of regions comprises: generating estimated request conversion scores for the plurality of transportation requests during the time period relative to the plurality of regions based on the locations of the plurality of transportation requests (Crapis, paragraph [0103]-[0105], conversion for a given area at a specified time interval is a function of the price multiplier and the ETA of the given area at the specified time interval; the price multiplier is based on available providers and the transportation requests in the neighborhood of the given area at specified time interval); and determining the accumulating regional metric for the provider device based on the estimated request conversion scores and the cumulative events metrics (Crapis, paragraph [0103]-[0108], applies the conversion function for the current number of providers in an area to the number of forecasted transportation requests for the area…; also see paragraph [0109]-[0111]).
Regarding claim 4, Crapis as modified by LU teach all claimed limitations as set forth in rejection of claim 2, further teach determining that the provider device is within the second region when generating the transportation match between the provider device and the requester device (Crapis, paragraph [0217], predict an offered incentive that corresponds to the predicted probability; the incentive is represented to a provider as an incremental accumulation metric, which increment as the provider travels toward the target area; also see Figs. 13A-13E and 14, paragraph [0307], determining that the current location of the transportation provider is within the second zone, and updating the accumulation interface portion to include the second color or the second pattern in association with the incremental accumulation metric; noted, as an indication of transportation provider; Fig. 13E-F illustrates the accumulative metrics that the driver would attain when the driver is in the hottest area; also see paragraph [0290], the transportation matching system updates the incentive instructions indicating to the provider that they have entered into the zone; also see paragraph [0301], upon initiating or completing the transportation request, the incremental metric can be awarded to the provider as a bonus; noted, matching the provider with the request when they have entered to the zone corresponding to the incremental metric; upon the initiating or completing the transportation request, awarding the provider with the incremental metric as bonus, which reads on as claimed).
Regarding claim 5, Crapis as modified by LU teach all claimed limitations as set forth in rejection of claim 4, further teach determining that the provider device remains online between obtaining the accumulating regional metric and generating the transportation match (Crapis, Figs. 13A-13E and 14, paragraph [0307], determining that the current location of the transportation provider is within the second zone, and updating the accumulation interface portion to include the second color or the second pattern in association with the incremental accumulation metric; noted, as an indication of transportation provider; Fig. 13E-F illustrates the accumulative metrics that the driver would attain when the driver is in the hottest area; also see paragraph [0290], the transportation matching system updates the incentive instructions indicating to the provider that they have entered into the zone; also see paragraph [0300]-[0301], an updated map of the provider’s location traveling within the inner zone; the incremental accumulation metric in Fig. 13F based on the time the provider spent in the inner zone; the transportation matching system matches the provider with a transportation request from the target area at or before the provider reach the maximum accumulation metric; noted, as the map on the provider device having updated accumulation metric when the driver enter in the hottest area and match the provider with the request before the accumulation metric reach its maximum value, which is an indication that the provider device remains online between obtaining the accumulating regional metric and generating the transportation match).
Regarding claim 7, Crapis as modified by LU teach all claimed limitations as set forth in rejection of claim 1, further teach wherein providing the accumulating regional metric map further comprises: determining an accumulating cluster metric for a subset of the plurality of regions utilizing a clustering model based on accumulating regional metrics for the plurality of regions during a time period (Crapis, paragraph [0066], a machine-learning model can include but not limited to, support vector machines, linear regression, logistic regression, Bayesian networks, clustering,…; also see paragraph [0068], the transportation flow matrix includes provider allocation values that forecast allocation shortages for areas at a future time interval); and providing an accumulating cluster pin for the subset of the plurality of regions with the accumulating cluster metric within the accumulating regional metric map (Crapis, paragraph [0237], the map includes a target areas 1002 (i.e., Area D3); the transportation matching system identifies the target area 1002 based on the generated transportation flow matrix; the transportation flow matrix 722 in Fig. 7C shows Area D2 as having allocation metric of “3”, which means that the target area 1002 is anticipated to have a provider shortage of three providers; also see also see fig. 4A-4B, as shown in Fig. 4A, each of the area in the region includes a forecast of provider 404 and transportation requests…).
Regarding claim 9, Crapis as modified by LU teach all claimed limitations as set forth in rejection of claim 7, further teach wherein providing the accumulating regional metric map further comprises: determining that a centroid of the subset of the plurality of regions is located outside a boundary of the subset of the plurality of regions (Crapis, paragraph [0072], creating inner zone corresponding to the boundary and an outer zone corresponding to the boundaries of the neighboring surrounding a target area; the width of the zone can be based on map distance, travel time, geographical features, or aligned with the boundaries of areas in the regions; also see paragraph [0170], employing distance-based approach in determining a neighborhood and a dispatch radius for a given area); and placing, within the boundary of the subset of the plurality of regions, the accumulating cluster pin at a position based on distances from edges of the subset of the plurality of regions (Crapis, paragraph [0262]-[0264], the target area is the epicenter of the map and the provider is located near an outer edge of the map; the size of the map is scaled to include the provider and the target area at the same time; also see paragraph [0262], expanding the outer zone to extend toward the provider’s current location such that the provider’s current location is near the edge of the outer zone).
As per claims 10 and 17, these claims are rejected on grounds corresponding to the same rationales given above for rejected claim 1 and are similarly rejected.
As per claim 11, this claim is rejected on grounds corresponding to the same rationales given above for rejected claim 2 and is similarly rejected.
Regarding claim 12, Crapis as modified by LU teach all claimed limitations as set forth in rejection of claim 11, further teach generating additional cumulative events metrics for additional regions within a proximity of the first region (Crapis, paragraph [0072], creating inner zone corresponding to the boundary and an outer zone corresponding to the boundaries of the neighboring surrounding a target area; the width of the zone can be based on map distance, travel time, geographical features, or aligned with the boundaries of areas in the regions; also see paragraph [0170], employing distance-based approach in determining a neighborhood and a dispatch radius for a given area; also see paragraph [0172], identifying second neighborhood and a second dispatch radius for the second area; using the travel time-based approach, determines area hat are within a shorter predetermined travel time of the boundary (or the center) of the second area to include in the neighborhood and areas within longer predetermined travel time of the boundary; identifies the areas 718a-718l to include in the second neighborhood; also see paragraph [0174], any provider in an area that is reached by the dispatch radius is included in the number of providers within a dispatch radius of a given area; the transportation matching system 102 only includes providers that have an ETA matching or shorter than the predetermined travel time; the number of providers within a dispatch radius of a given area only include providers that can travel to the given area (or at least the area's neighborhood) within the predetermined travel time); and determining the accumulating regional metric for the provider device based further on the additional cumulative events metrics for the additional regions according to a geospatial smoothing model (Crapis, paragraph [01111], apply or weight the incremental provider metric using one or more previous incremental metric (e.g., a smoothing metric) to smooth the incremental provider metric from one time interval to the next).
Regarding claim 13, Crapis as modified by LU teach all claimed limitations as set forth in rejection of claim 11, further teach comprising instructions that, when executed by the at least one processor, cause the system to provide the accumulating regional metric map by: generating an accumulating metric pin of the plurality of accumulating metric pins corresponding to the first region and an additional region adjacent to the first region based on the cumulative events metric for the first region and an additional cumulative events metric for the additional region (Crapis, paragraph [0072], creating inner zone corresponding to the boundary and an outer zone corresponding to the boundaries of the neighboring surrounding a target area; the width of the zone can be based on map distance, travel time, geographical features, or aligned with the boundaries of areas in the regions; also see paragraph [0170], employing distance-based approach in determining a neighborhood and a dispatch radius for a given area; also see paragraph [0172], identifying second neighborhood and a second dispatch radius for the second area; using the travel time-based approach, determines area hat are within a shorter predetermined travel time of the boundary (or the center) of the second area to include in the neighborhood and areas within longer predetermined travel time of the boundary; identifies the areas 718a-718l to include in the second neighborhood; also see paragraph [0174], any provider in an area that is reached by the dispatch radius is included in the number of providers within a dispatch radius of a given area; the transportation matching system 102 only includes providers that have an ETA matching or shorter than the predetermined travel time; the number of providers within a dispatch radius of a given area only include providers that can travel to the given area (or at least the area's neighborhood) within the predetermined travel time); and determining a placement location for the accumulating metric pin based on a size and a position of a combined region comprising the first region and the additional region (Crapis, paragraph [0072], creating inner zone corresponding to the boundary and an outer zone corresponding to the boundaries of the neighboring surrounding a target area; the width of the zone can be based on map distance, travel time, geographical features, or aligned with the boundaries of areas in the regions; also see paragraph [0170], employing distance-based approach in determining a neighborhood and a dispatch radius for a given area; also see paragraph [0172], identifying second neighborhood and a second dispatch radius for the second area; using the travel time-based approach, determines area hat are within a shorter predetermined travel time of the boundary (or the center) of the second area to include in the neighborhood and areas within longer predetermined travel time of the boundary; identifies the areas 718a-718l to include in the second neighborhood; also see paragraph [0174], any provider in an area that is reached by the dispatch radius is included in the number of providers within a dispatch radius of a given area; the transportation matching system 102 only includes providers that have an ETA matching or shorter than the predetermined travel time; the number of providers within a dispatch radius of a given area only include providers that can travel to the given area (or at least the area's neighborhood) within the predetermined travel time; also see paragraph [0262]-[0264], the target area is the epicenter of the map and the provider is located near an outer edge of the map; the size of the map is scaled to include the provider and the target area at the same time; also see paragraph [0262], expanding the outer zone to extend toward the provider’s current location such that the provider’s current location is near the edge of the outer zone).
Regarding claim 15, Crapis as modified by LU teach all claimed limitations as set forth in rejection of claim 10, further teach comprising instructions that, when executed by the at least one processor, cause the system to determine the accumulating regional metric for the provider device by: determining that the provider device moves to an additional region of the plurality of regions (Crapis, paragraph [0179], each time a provider is relocated from a first area to the second area…);determining that the accumulating regional metric corresponding to the accumulating metric pin of the first region is greater than an additional accumulating regional metric corresponding to an additional accumulating regional metric pin of the additional region (Crapis, paragraph [0179], verify that the benefit or incremental effect gained by adding the provider to the second area outweighs that benefit lost by the first area; compare incremental provider metrics between the first area and the second area and confirms that the difference between the incremental provider metrics satisfies an incremental threshold; if the change in benefit is negligible or below the benefits threshold, determines if the cost of moving the provider outweighs the benefit); and selecting the accumulating regional metric corresponding to the accumulating metric pin of the first region for the provider device (Crapis, paragraph [0179], verify that the benefit or incremental effect gained by adding the provider to the second area outweighs that benefit lost by the first area; compare incremental provider metrics between the first area and the second area and confirms that the difference between the incremental provider metrics satisfies an incremental threshold; if the change in benefit is negligible or below the benefits threshold, determines if the cost of moving the provider outweighs the benefit; also see paragraph [0230], select target area that will yield the most significant benefit; also see paragraph [0133] and [0136]).
Regarding claim 16, Crapis as modified by LU teach all claimed limitations as set forth in rejection of claim 10, further teach: comprising instructions that, when executed by the at least one processor, cause the system to: generate the transportation match for the provider device involving a transportation request associated with the requester device after determining the accumulating regional metric for the provider device (Crapis, paragraph [0239]-[0240], identifying each of the capable providers within the target area dispatch radius that is capable of fulfilling a transportation request in the target area during the future time interval; each of capable providers is labeled with probability that the provider will travel to the target area to fulfill a transportation request; also see paragraph [0200], after one or more providers are selected for an area, or after provider are selected for all target areas, the transportation matching system can send relocating requests to each of the selected drivers; also see paragraph [0217], predict an offered incentive that corresponds to the predicted probability; the incentive is represented to a provider as an incremental accumulation metric, which increment as the provider travels toward the target area); and modify a transportation provider metric associated with the transportation request based on the accumulating regional metric (Crapis, paragraph [0108], training and utilizing the incremental provider model to produce an incremental provider metric corresponding to adding a single provider (or any fix number) to each region; applies the conversion function to current number of providers in an area to the number of forecasted transportation request for the area (and a specified time interval)…).
Regarding claim 18, Crapis as modified by LU teach all claimed limitations as set forth in rejection of claim 17, further teach further comprising instructions that, when executed by the at least one processor, cause the computing device to determine the accumulating regional metric for the provider device by: determining locations of a plurality of transportation requests within the first region for a time period (Crapis, paragraph [0064], the term “real-time transportation request forecast” refers to anticipated transportation requests for a time interval in the near future for one or more regions; also see paragraph [0083], identifying forecast of providers and transportation requests for a geocoded region);
generating a cumulative events metric for the first region during the time period based on the locations of the plurality of transportation requests (Crapis, paragraph [0083], identifying forecast of providers and transportation requests for a geocoded region; also see paragraph [0064], the term “real-time transportation request forecast” refers to anticipated transportation requests for a time interval in the near future for one or more regions; also see paragraph [0237], the map includes a target areas 1002 (i.e., Area D3); the transportation matching system identifies the target area 1002 based on the generated transportation flow matrix; the transportation flow matrix 722 in Fig. 7C shows Area D2 as having allocation metric of “3”, which means that the target area 1002 is anticipated to have a provider shortage of three providers; also see also see fig. 4A-4B, as shown in Fig. 4A, each of the area in the region includes a forecast of provider 404 and transportation requests);
generating estimated request conversion scores for the plurality of transportation requests during the time period (Crapis, paragraph [0103]-[0105], conversion for a given area at a specified time interval is a function of the price multiplier and the ETA of the given area at the specified time interval; the price multiplier is based on available providers and the transportation requests in the neighborhood of the given area at specified time interval); and
determining the accumulating regional metric for the provider device based on the cumulative events metric for the first region and the estimated request conversion scores (Crapis, paragraph [0103]-[0108], applies the conversion function for the current number of providers in an area to the number of forecasted transportation requests for the area…; also see paragraph [0109]-[0111]).
Regarding claim 19, Crapis as modified by LU teach all claimed limitations as set forth in rejection of claim 18, further teach comprising instructions that, when executed by the at least one processor, cause the computing device to determine the accumulating regional metric for the provider device by utilizing a geospatial smoothing model to determine a contribution of a plurality of cumulative events metrics for a plurality of adjacent regions based on relative predicted conversion probabilities of a set of transportation requests in the plurality of adjacent regions (Crapis, paragraph [01111], apply or weight the incremental provider metric using one or more previous incremental metric (e.g., a smoothing metric) to smooth the incremental provider metric from one time interval to the next).
Regarding claim 20, Crapis as modified by LU teach all claimed limitations as set forth in rejection of claim 17, further teach comprising instructions that, when executed by the at least one processor, cause the computing device to provide the accumulating regional metric map by determining a placement location for an accumulating metric pin of the plurality of accumulating metric pins based on a size or a shape of a combined region for a subset of regions of the plurality of regions (Crapis, paragraph [0072], creating inner zone corresponding to the boundary and an outer zone corresponding to the boundaries of the neighboring surrounding a target area; the width of the zone can be based on map distance, travel time, geographical features, or aligned with the boundaries of areas in the regions; also see paragraph [0170], employing distance-based approach in determining a neighborhood and a dispatch radius for a given area; also see paragraph [0262]-[0264], the target area is the epicenter of the map and the provider is located near an outer edge of the map; the size of the map is scaled to include the provider and the target area at the same time; also see paragraph [0262], expanding the outer zone to extend toward the provider’s current location such that the provider’s current location is near the edge of the outer zone).
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Crapis et al. (U.S. Pub. 2020/0082315 A1) in view of LU et al. (“Surge pricing Moves Uber’s Driver-Partner”; School of Operations Research and Information Engineering, Cornell University; May 17, 2018), further in view of Levi (U.S. Pub. No. 2020/0219220 A1).
Regarding claim 6, Crapis as modified by LU teach all claimed limitations as set forth in rejection of claim 2, but do not explicitly disclose: providing the accumulating regional metric map to the provider device while the provider device is in an offline mode; and wherein determining the accumulating regional metric for the provider device comprises determining that the provider device is online.
Levi teaches: providing the accumulating regional metric map to the provider device while the provider device is in an offline mode (Fig. 5A-5D, paragraph [0085]-[0087], in Fig. 5B and Fig. 5C, the counter value is shown to increase, reflecting the service provider continuing in the off-service state; noted, off-service state is interpreted “offline mode”); and wherein determining the accumulating regional metric for the provider device comprises determining that the provider device is online (Fig. 5A-5D, paragraph [0085]-[0087], in Fig. 5A, on online feature may provide on a user interface of a service provider’s mobile device; the user may interact with the online feature to transition the service provider to an online and unmatched state; also see paragraph [0048], the counter manager may monitor the service data store for one or more milestones (e.g., a predetermined change to the service state of the service provider); the milestone may coincide with, for example, the service provider going online).
It would have been obvious to one of ordinary skill in art before the effective filing date of the claim invention to include providing the accumulating regional metric map to the provider device while the provider device is in an offline mode; and wherein determining the accumulating regional metric for the provider device comprises determining that the provider device is online into ride-sharing application of Crapis.
Motivation to do so would be to include providing the accumulating regional metric map to the provider device while the provider device is in an offline mode; and wherein determining the accumulating regional metric for the provider device comprises determining that the provider device is online that is able to better determine and manage provisioning levels over a given geographic region (Levi, paragraph [0014], line 12-14).
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Crapis et al. (U.S. Pub. 2020/0082315 A1) in view of LU et al. (“Surge pricing Moves Uber’s Driver-Partner”; School of Operations Research and Information Engineering, Cornell University; May 17, 2018), further in view of Deskevich (U.S. Pub. No. 2019/0295259 A1).
Regarding claim 8, Crapis as modified by LU teach all claimed limitations as set forth in rejection of claim 7, but do not explicitly disclose: determining that a size or a shape of the subset of the plurality of regions does not meet a threshold size or a threshold shape; recursively dividing the subset of the plurality of regions into a plurality of subdivisions until a particular subdivision of the plurality of subdivisions meets the threshold size or the threshold shape.
Deskevich teaches: determining that a size or a shape of the subset of the plurality of regions does not meet a threshold size or a threshold shape (paragraph [0047], the region A and B are checked to determine whether they are the less than or equal to the desired threshold; the threshold is measured in units of surface area (e.g., square feet, square meters)); recursively dividing the subset of the plurality of regions into a plurality of subdivisions until a particular subdivision of the plurality of subdivisions meets the threshold size or the threshold shape (paragraph [0048], if the regions A and B are not less than the threshold, the process repeats on each sub-region A and B, to further divide each in to sub-regions of approximately equal compact size and minimal perimeter; also see paragraph [0049], if the regions A and B are less than or equal to the threshold, the process is completed and the sub-regions are compact, approximately equal size and with a minimal perimeter; also see paragraph [0033]).
It would have been obvious to one of ordinary skill in art before the effective filing date of the claim invention to include determining that a size or a shape of the subset of the plurality of regions does not meet a threshold size or a threshold shape; recursively dividing the subset of the plurality of regions into a plurality of subdivisions until a particular subdivision of the plurality of subdivisions meets the threshold size or the threshold shape into zones division of Crapis.
Motivation to do so would be to include determining that a size or a shape of the subset of the plurality of regions does not meet a threshold size or a threshold shape; recursively dividing the subset of the plurality of regions into a plurality of subdivisions until a particular subdivision of the plurality of subdivisions meets the threshold size or the threshold shape to overcome downsides of conventional method such as it is possible for the area of subdivision to vary dramatically; also, the subregions are not compact, and the perimeters of each are longer than they would need to be (Deskevich, paragraph [0008], line 1-5).
Crapis as modified by LU and Deskevich further teach: providing subdivision accumulating metric pins for the plurality of subdivisions within the accumulating regional metric map (Crapis, paragraph [0044], generating customized provider interface that includes a mapping interface portion and an accumulation interface portion; the mapping interface includes a map of the target area as well as the current location of the provider; the map portion includes one or more zones that center a target area; the accumulation interface portion includes an incremental bonus metric that increases as the provider approaches the target area and/or based on the time that the provider stays in each of the zones; also see fig. 4A-4B, as shown in Fig. 4A, each of the area in the region includes a forecast of provider 404 and transportation requests…; also see paragraph [0237], the map includes a target areas 1002 (i.e., Area D3); the transportation matching system identifies the target area 1