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 .
Response to Amendment
Applicant submitted amendments and remarks on September 22, 2025. Therein, Applicant submitted substantive arguments. Claims 1 and 10 have been amended. No claims were added or cancelled.
The submitted claims are considered below.
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.
Claims 1-8, 10-17, and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Dean, et al. (U.S. Patent No. 11333503) in view of Kundu, et al. (U.S. Patent Application Publication No. 20230080281).
Regarding claim 1, Dean, et al. teaches: A method of controlling an autonomous vehicle, the method comprising: receiving, by one or more processors, dispatching instructions including a destination location and a trip plan identifying aspects of a selected route, (Step (402), Fig. 4, Col. 25, lines 19-29: "…process (400) includes receiving map data associated with a map of a geographic location including a global route in one or more roadways between a current location of an AV and a destination location of the AV [instructions including destination location and trip plan by processor].")
using, by the one or more processors, the trip plan to plan a route locally at the autonomous vehicle; (Step (404), Fig. 4, Col. 28, lines 31-36: "…determining, based on the map data, one or more local routes in the one or more roadways between a starting location and one or more exit locations [planning a route locally], […] starting location of the AV and the destination location of the AV [autonomous vehicle].")
and controlling, by the one or more processors, the autonomous vehicle to the destination location based on the planned route (Step (408), Fig. 4, Col. 32, lines 41-47: "…a processing time and/or a resource usage of an AV (e.g., one or more systems or devices of an AV, etc.) [using processors] […] control travel [controlling] of an autonomous vehicle (104) between a starting location and a destination location of the AV [autonomous vehicle to destination location based on planned route].").
displayed to the user (Col. 24, lines 26-28: "Output component (312) [output component to user] includes a component that provides output information from device (300) (e.g., a display [display]").
Dean, et al. does not explicitly teach the process of selecting a route by a user from a set of two or more routes. However, Dean, et al. teaches the process of how a local route can be selected by the map generation system (102) or the vehicle computing system (106) from one or more local routes based on a preference by a user (Col. 32, lines 4-12). This is equivalent to the claim limitation at issue since the descriptions of the route set sizes are unlimited in size and overlap each other in scope. Therefore, this teaching would have made it obvious to modify Dean, et al. to include the process of selecting a route by a user from a set of two or more routes based on the motivation to improve the process of controlling the navigation of an autonomous vehicle.
Dean, et al. does not teach and enforcing, by the one or more processors during the controlling, the trip plan by inhibiting route optimization recalculation.
In a similar field of endeavor (vehicle routing), Kundu, et al. teaches: and enforcing, by the one or more processors during the controlling, the trip plan by inhibiting route optimization recalculation (Paragraph [0166]: "…with respect to FIG. 5, the POZ determining process executed by the predictive analytics module(s) (150) [processors] may determine the POZ for all road segments of each candidate route. The POZ determinations may be performed sequentially or in parallel. In addition, the POZs determined for the respective road segments may be stored in the databases (154) for future use, such as in the map data database (156), or the like. Accordingly, when the POZ of a road segment under consideration is available in the map data database (156), the system may utilize the stored POZ rather than having to recalculate the POZ [inhibiting route optimization calculation] [...] "When the POZs for all the road segments for a particular candidate route have been determined, an average percentage may be calculated for the candidate route by averaging the percentage of overlap of the POZs by the FOY for all road segments for that candidate route. The average percentage may be used as the safety score of the candidate route in some implementations herein. The candidate route that provides the highest percentage may indicate the safest route for the particular vehicle, such as based on maximizing the amount of automated driving time [Background Information - Using Precautionary Observation Zone (POZ) methodology to calculate route optimization - before inhibition].").
Therefore, it would have been obvious to one of the ordinary skill of the art before the effective filing date of the claimed invention to modify Dean, et al. to include the teaching of Kundu, et al. based on a reasonable expectation of success and motivation to improve the process of controlling the optimization of the routing of autonomous vehicles (Kundu, et al. Paragraph [0026]).
Regarding claim 2, Dean, et al. and Kundu, et al. remain as applied to claim 1, and in a further embodiment, teaches: The method of claim 1, wherein the trip plan further identifies a plurality of identifiers for road segments which when connected together with a pickup location and the destination location correspond to the selected route (Dean, et al. Col. 37, lines 45-50: "…vehicle computing system (106) receives one or more route elements [selected route] […] segments of a roadway [road segments] between a starting location [pickup location] and an exit location [destination location].").
Regarding claim 3, Dean, et al. and Kundu, et al. remains as applied to claim 1, and in a further embodiment, teaches: The method of claim 1, wherein the trip plan further identifies a plurality of geographic locations which when connected together with a pickup location and the destination location correspond to the selected route (Dean, et al. Step (404), Fig. 4, Col. 28, lines 31-36: "…one or more local routes in the one or more roadways between a starting location and one or more exit locations, wherein the one or more exit locations are located between the starting location of the AV and the destination location of the AV [plurality of geographic locations are connected between pickup and destination location for route].").
Regarding claim 4, the combination of Dean, et al. and Kundu, et al. does not explicitly teach the process in which two or more of the plurality of geographic locations are a fixed distance from one another. However, Dean, et al. teaches the process on how the computing system (106) can select one or more exit locations that are located at a specific predetermined distance from a starting location (Col. 30, lines 39-46). This is equivalent to the claim limitation at issue since the descriptions of the geographic location set sizes are unlimited in size and overlap each other in scope. Therefore, this teaching would have made it obvious to modify the combination of Dean, et al. and Kundu, et al. to include the process in which two or more of the plurality of geographic locations are a fixed distance from one another based on the motivation to improve the process of controlling the navigation of an autonomous vehicle.
Regarding claim 5, Dean, et al. and Kundu, et al. remain as applied to claim 1, and in a further embodiment, teaches: The method of claim 1, wherein the trip plan further identifies a geographic location between the pickup location and the destination location on the selected route, (Dean, et al. Step (502), Col. 32, lines 61-66: "…includes determining one or more exit locations based on a threshold distance and the current location of the AV [identifies geographic location between pickup location and destination location on route].")
and the method further comprises: generating routes based on a current location of the autonomous vehicle and the destination location; (Dean, et al. Step (502), Col. 32, lines 61-63: "…determining one or more exit locations based on a threshold distance and the current location of the AV [based on current location of autonomous vehicle and destination location]." ; Dean, et al. Step (504), Col. 33, lines 44-51: "…determines a plurality of candidate local routes, in the one or more roadways, for each exit location of the one or more exit locations [generates routes]")
and determining costs for the generated routes by adding an additional cost to each of the generated routes which do not pass through the identified geographic location, (Dean, et al. Col. 28, lines 14-16: "…a lane in the global route may have a cost in a cost field that is less than a cost in a cost field for a lane not in the global route [higher cost is assigned to route that does not pass through identified geographic location].")
and wherein determining whether to use the selected route or a new route is based on the determined costs (Dean, et al. Col. 34, lines 33-42: "…determines one or more diversion points based on determining a change in lane identifier associated with a lower cost route on the forks [judgment made based on determined costs]. For example, a change in lane identifier along with a lower cost route extending from a diversion point (e.g., a fork in route, etc.) may refer to a diversion point in the local graph where the route diverges (e.g., forks, splits, etc.) from a single route into at least two routes [selection of existing route or new route]").
Regarding claim 6, Dean, et al. remains as applied to claim 1, and in a further embodiment, teaches: The method of claim 1, wherein the trip plan further identifies a geographic location between a pickup location and the destination location for each route of the set of routes, (Dean, et al. Step (508), Fig. 5, Col. 34, lines 51-53: "…determining lanes in candidate local routes for each exit location [identifies location between starting pickup and destination location for each route].")
and the method further comprises: generating routes based on a current location of the autonomous vehicle and the destination location; (Dean, et al. Step (502), Col. 32, lines 61-63: "…determining one or more exit locations based on a threshold distance and the current location of the AV [based on current location of autonomous vehicle and destination location]." ; Dean, et al. Step (504), Col. 33, lines 44-51: "…determines a plurality of candidate local routes, in the one or more roadways, for each exit location of the one or more exit locations [generates routes]")
and determining costs for the generated routes by adding an additional cost to each of the generated routes which pass through the identified geographic locations for routes of the set of routes other than the selected route, (Dean, et al. Col. 34, lines 42-48: "…lower cost paths on the forks provides efficiency and accuracy by eliminating creation of any diversion point where a new path includes a higher cost than a current path [identifies higher cost regions for alternative routes and eliminates them for efficiency].")
and wherein determining whether to use the selected route or a new route is based on the determined costs (Dean, et al. Col. 34, lines 33-42: "…determines one or more diversion points based on determining a change in lane identifier associated with a lower cost route on the forks [judgment made based on determined costs]. For example, a change in lane identifier along with a lower cost route extending from a diversion point (e.g., a fork in route, etc.) may refer to a diversion point in the local graph where the route diverges (e.g., forks, splits, etc.) from a single route into at least two routes [selection of existing route or new route]").
Regarding claim 7, Dean, et al. and Kundu, et al. remain as applied to claim 1, and in a further embodiment, teaches: The method of claim 1, wherein the trip plan further identifies a plurality of geographic locations for each given route of the set of routes which when connected together with a pickup location and the destination location correspond to the given route (Dean, et al. Step (404), Fig. 4, Col. 28, lines 31-36: "…one or more roadways between a starting location and one or more exit locations, wherein the one or more exit locations are located between the starting location of the AV and the destination location of the AV [plurality of geographic locations are connected between pickup and destination location for route]." ; Dean, et al. Col. 27, lines 17-21: "…global route associated with each route of a plurality of routes [each route in the set of routes] in a geographic location between a starting location and a destination location.")
and the method further comprises: generating routes based on a current location of the autonomous vehicle and the destination location; (Dean, et al. Step (502), Col. 32, lines 61-63: "…determining one or more exit locations based on a threshold distance and the current location of the AV [based on current location of autonomous vehicle and destination location]." ; Dean, et al. Step (504), Col. 33, lines 44-51: "…determines a plurality of candidate local routes, in the one or more roadways, for each exit location of the one or more exit locations [generates routes]")
and determining costs for the generated routes by adding an additional cost to each of the generated routes which pass within a radial distance of any of the identified geographic locations for routes of the set of routes, (Dean, et al. Col. 33, lines 5-9: "…map generation system (102) and/or vehicle computing system (106) may determine one or more exit locations in a cost field associated with a global route [identified geographic locations for routes based in set of routes] based on a sensor horizon (e.g., within a threshold distance of a sensor horizon) [pass though radial distance]." ; Dean, et al. Step (808), Fig. 8, Col 46, lines 9-18: "…adjusting costs of local routes associated with the global route to the destination location and determining local routes or roadways that satisfy one or more threshold costs for the coverage route [adding costs to created routes].")
and wherein determining whether to use the selected route or a new route is based on the determined costs (Dean, et al. Col. 34, lines 33-42: "…determines one or more diversion points based on determining a change in lane identifier associated with a lower cost route on the forks [judgment made based on determined costs]. For example, a change in lane identifier along with a lower cost route extending from a diversion point (e.g., a fork in route, etc.) may refer to a diversion point in the local graph where the route diverges (e.g., forks, splits, etc.) from a single route into at least two routes [selection of existing route or new route]").
Regarding claim 8, Dean, et al. and Kundu, et al. remain as applied to claim 1, and in a further embodiment, teaches: The method of claim 1, wherein the trip plan further identifies a plurality of geographic locations for each given route of the set of routes which when connected together with a pickup location and the destination location correspond to the given route, (Dean, et al. Step (404), Fig. 4, Col. 28, lines 31-36: "…one or more local routes in the one or more roadways between a starting location and one or more exit locations, wherein the one or more exit locations are located between the starting location of the AV and the destination location of the AV [plurality of geographic locations are connected between pickup and destination location for route]." ; Dean, et al. Col. 27, lines 17-21: "…global route associated with each route of a plurality of routes [each route in the set of routes] in a geographic location between a starting location and a destination location.")
and the method further comprises: generating routes based on a current location of the autonomous vehicle and the destination location; (Dean, et al. Step (502), Col. 32, lines 61-63: "…determining one or more exit locations based on a threshold distance and the current location of the AV [based on current location of autonomous vehicle and destination location]." ; Dean, et al. Step (504), Col. 33, lines 44-51: "…determines a plurality of candidate local routes, in the one or more roadways, for each exit location of the one or more exit locations [generates routes]")
and determining costs for the generated routes by adding an additional cost to each of the generated routes which pass within a radial distance of any of the identified geographic locations for routes of the set of routes other than the selected route, (Dean, et al. Col. 33, lines 5-9: "…map generation system (102) and/or vehicle computing system (106) may determine one or more exit locations in a cost field associated with a global route [identified geographic locations for routes based in set of routes] based on a sensor horizon (e.g., within a threshold distance of a sensor horizon) [pass though radial distance]." ; Dean, et al. Col. 34, lines 45-48: "…lower cost paths on the forks provides efficiency and accuracy by eliminating creation of any diversion point where a new path includes a higher cost than a current path [adding additional cost to routes that pass through routes other than selected route; filters out these routes].")
and wherein determining whether to use the selected route or a new route is based on the determined costs (Dean, et al. Col. 34, lines 33-42: "…determines one or more diversion points based on determining a change in lane identifier associated with a lower cost route on the forks [judgment made based on determined costs]. For example, a change in lane identifier along with a lower cost route extending from a diversion point (e.g., a fork in route, etc.) may refer to a diversion point in the local graph where the route diverges (e.g., forks, splits, etc.) from a single route into at least two routes [selection of existing route or new route]").
Regarding claim 10, Dean, et al. teaches: A system for controlling an autonomous vehicle, (Fig. 2, Col. 19, lines 33-35: "…diagram of a non-limiting embodiment of a system (200) for controlling autonomous vehicle (104) [system for controlling an autonomous vehicle].")
the system comprising one or more processors configured to: (Col. 18, lines 36-39: "…one or more computing systems, including one or more processors (e.g., one or more servers, etc.) [processors].")
receive dispatching instructions including a destination location and a trip plan identifying a selected route, (Col. 25, lines 23-32: "…map generation system (102) and/or autonomous vehicle (104) (e.g., vehicle computing system (106), etc.) receives map data associated with a map of a geographic location, wherein the map data includes a global route between a starting location associated with autonomous vehicle (104) (e.g., a current location of autonomous vehicle (104), a pickup location, etc.) and a destination location associated with autonomous vehicle (104) (e.g., a target location of autonomous vehicle (104), a drop-off location, etc.) [instructions including destination location and trip plan by processor]")
displayed to the user; (Col. 24, lines 26-28: "Output component (312) [output component to user] includes a component that provides output information from device (300) (e.g., a display [display]")
use the trip plan to plan a route locally at the autonomous vehicle; (Col. 28, lines 36-46: "…determines, based on the map data, a plurality of local routes (e.g., a route option in a global cost field, a portion of a global route, an alternative to a global route, etc.) in one or more roadways between a starting location of autonomous vehicle (104) (e.g., a current location of autonomous vehicle (104), etc.) and a plurality of exit locations [planning a route locally] that are located between a starting location of the AV and a destination location of the AV [autonomous vehicle].")
control the autonomous vehicle to the destination location based on the determination (Col. 32, lines 41-47: "…a processing time and/or a resource usage of an AV (e.g., one or more systems or devices of an AV, etc.) [using processors] […] control travel [controlling] of an autonomous vehicle (104) between a starting location and a destination location of the AV [autonomous vehicle to destination location based on determination].").
Dean, et al. does not explicitly teach the process of selecting a route by a user from a set of two or more routes. However, Dean, et al. teaches the process of how a local route can be selected by the map generation system (102) or the vehicle computing system (106) from one or more local routes based on a preference by a user (Col. 32, lines 4-12). This is equivalent to the claim limitation at issue since the descriptions of the route set sizes are unlimited in size and overlap each other in scope. Therefore, this teaching would have made it obvious to modify Dean, et al. to include the process of selecting a route by a user from a set of two or more routes based on the motivation to improve the process of controlling the navigation of an autonomous vehicle.
Dean, et al. does not teach and enforce, during the control of the autonomous vehicle to the destination location, the trip plan by inhibiting route optimization recalculation.
In a similar field of endeavor (vehicle routing), Kundu, et al. teaches: and enforce, during the control of the autonomous vehicle to the destination location, the trip plan by inhibiting route optimization recalculation (Paragraph [0166]: "…with respect to FIG. 5, the POZ determining process executed by the predictive analytics module(s) (150) [processors] may determine the POZ for all road segments of each candidate route. The POZ determinations may be performed sequentially or in parallel. In addition, the POZs determined for the respective road segments may be stored in the databases (154) for future use, such as in the map data database (156), or the like. Accordingly, when the POZ of a road segment under consideration is available in the map data database (156), the system may utilize the stored POZ rather than having to recalculate the POZ [inhibiting route optimization calculation] [...] "When the POZs for all the road segments for a particular candidate route have been determined, an average percentage may be calculated for the candidate route by averaging the percentage of overlap of the POZs by the FOY for all road segments for that candidate route. The average percentage may be used as the safety score of the candidate route in some implementations herein. The candidate route that provides the highest percentage may indicate the safest route for the particular vehicle, such as based on maximizing the amount of automated driving time [Background Information - Using Precautionary Observation Zone (POZ) methodology to calculate route optimization - before inhibition].").
Therefore, it would have been obvious to one of the ordinary skill of the art before the effective filing date of the claimed invention to modify Dean, et al. to include the teaching of Kundu, et al. based on a reasonable expectation of success and motivation to improve the process of controlling the optimization of the routing of autonomous vehicles (Kundu, et al. Paragraph [0026]).
Regarding claim 11, Dean, et al. and Kundu, et al. remain as applied to claim 10, and in a further embodiment, teaches: The system of claim 10, wherein the trip plan further identifies a plurality of identifiers for road segments which when connected together with a pickup location and the destination location correspond to the selected route (Dean, et al. Col. 37, lines 45-50: "…vehicle computing system (106) receives one or more route elements [selected route] […] segments of a roadway [road segments] between a starting location [pickup location] and an exit location [destination location].").
Regarding claim 12, Dean, et al. and Kundu, et al. remains as applied to claim 10, and in a further embodiment, teaches: The system of claim 10, wherein the trip plan further identifies a plurality of geographic locations which when connected together with a pickup location and the destination location correspond to the selected route (Dean, et al. Col. 28, lines 36-46: "…determines, based on the map data, a plurality of local routes (e.g., a route option in a global cost field, a portion of a global route, an alternative to a global route, etc.) in one or more roadways between a starting location of autonomous vehicle (104) (e.g., a current location of autonomous vehicle (104), etc.) and a plurality of exit locations that are located between a starting location of the AV and a destination location of the AV [plurality of geographic locations are connected between pickup and destination location for route].").
Regarding claim 13, Dean, et al. and Kundu, et al. does not explicitly teach the process in which two or more of the plurality of geographic locations are a fixed distance from one another. However, Dean, et al. teaches the process on how the computing system (106) can select one or more exit locations that are located at a specific predetermined distance from a starting location (Col. 30, lines 39-46). This is equivalent to the claim limitation at issue since the descriptions of the geographic location set sizes are unlimited in size and overlap each other in scope. Therefore, this teaching would have made it obvious to modify Dean, et al. and Kundu, et al. to include the process in which two or more of the plurality of geographic locations are a fixed distance from one another based on the motivation to improve the process of controlling the navigation of an autonomous vehicle.
Regarding claim 14, Dean, et al. and Kundu, et al. remains as applied to claim 10, and in a further embodiment, teaches: The system of claim 10, wherein the trip plan further identifies a geographic location between a pickup location and the destination location on the selected route, and the one or more processors are further configured to: (Dean, et al. Col. 32, lines 61-66: "…map generation system (102) and/or vehicle computing system (106) determines one or more exit locations of the global route at a predetermined distance (e.g., at a threshold distance from the starting location, at a threshold distance from a current location of autonomous vehicle (104), etc.) [identifies geographic location between pickup location and destination location on route].")
generate routes based on a current location of the autonomous vehicle and the destination location; (Dean, et al. Col. 32, line 64 to Col. 33, lines 1-5: "…map generation system (102) and/or vehicle computing system (106) determines one or more exit locations of the global route at a predetermined distance (e.g., at a threshold distance from the starting location, at a threshold distance from a current location of autonomous vehicle (104), etc.) [based on current location of autonomous vehicle and destination location." ; Dean, et al. Col. 33, lines 47-51: "…determines a plurality of candidate local routes, in the one or more roadways, for each exit location of the one or more exit locations [generates routes].")
and determine costs for the generated routes by adding an additional cost to each of the generated routes which do not pass through the identified geographic location, (Dean, et al. Col. 28, lines 14-16: "…a lane in the global route may have a cost in a cost field that is less than a cost in a cost field for a lane not in the global route [higher cost is assigned to route that does not pass through identified geographic location].")
and wherein determining whether to use the selected route or a new route is based on the determined costs (Dean, et al. Col. 34, lines 33-42: "…determines one or more diversion points based on determining a change in lane identifier associated with a lower cost route on the forks [judgment made based on determined costs]. For example, a change in lane identifier along with a lower cost route extending from a diversion point (e.g., a fork in route, etc.) may refer to a diversion point in the local graph where the route diverges (e.g., forks, splits, etc.) from a single route into at least two routes [selection of existing route or new route]").
Regarding claim 15, Dean, et al. and Kundu, et al. remain as applied to claim 10, and in a further embodiment, teaches: The system of claim 10, wherein the trip plan further identifies a geographic location between a pickup location and the destination location for each route of the set of routes, and the one or more processors are further configured to: (Dean, et al. Col. 34, lines 53-59: "…map generation system (102) and/or vehicle computing system (106) determines one or more lanes (e.g., routable lanes traversed within a route element), as well as alternative lanes (e.g., routable lanes that may not be traversed within a route element) within the same segment of roadway based on the cost field associated with the global route for controlling an autonomous vehicle (104) [identifies location between staring pickup and destination location for each route].")
generate routes based on a current location of the autonomous vehicle and the destination location; (Dean, et al. Col. 32, line 64 to Col. 33, lines 1-5: "…map generation system (102) and/or vehicle computing system (106) determines one or more exit locations of the global route at a predetermined distance (e.g., at a threshold distance from the starting location, at a threshold distance from a current location of autonomous vehicle (104), etc.) [based on current location of autonomous vehicle and destination location." ; Dean, et al. Col. 33, lines 47-51: "…determines a plurality of candidate local routes, in the one or more roadways, for each exit location of the one or more exit locations [generates routes].")
and determine costs for the generated routes by adding an additional cost to each of the generated routes which pass through the identified geographic locations for routes of the set of routes other than the selected route, (Dean, et al. Col. 34, lines 42-48: "…lower cost paths on the forks provides efficiency and accuracy by eliminating creation of any diversion point where a new path includes a higher cost than a current path [identifies higher cost regions for alternative routes and eliminates them for efficiency].")
and wherein determining whether to use the selected route or a new route is based on the determined costs (Dean, et al. Col. 34, lines 33-42: "…determines one or more diversion points based on determining a change in lane identifier associated with a lower cost route on the forks [judgment made based on determined costs]. For example, a change in lane identifier along with a lower cost route extending from a diversion point (e.g., a fork in route, etc.) may refer to a diversion point in the local graph where the route diverges (e.g., forks, splits, etc.) from a single route into at least two routes [selection of existing route or new route]").
Regarding claim 16, Dean, et al. remains as applied to claim 10, and in a further embodiment, teaches: The system of claim 10, wherein the trip plan further identifies a plurality of geographic locations for each given route of the set of routes which when connected together with a pickup location and the destination location correspond to the given route, and the one or more processors are further configured to: (Dean, et al. Col. 28, lines 37-47: "…a plurality of local routes (e.g., a route option in a global cost field, a portion of a global route, an alternative to a global route, etc.) in one or more roadways between a starting location of autonomous vehicle (104) (e.g., a current location of autonomous vehicle (104), etc.) and a plurality of exit locations that are located between a starting location of the AV and a destination location of the AV [plurality of geographic locations are connected between pickup and destination location for route]." ; Dean, et al. Col. 27, lines 17-21: "…a global route associated with each route of a plurality of routes [each route in the set of routes] in a geographic location between a starting location and a destination location.")
generate routes based on a current location of the autonomous vehicle and the destination location; (Dean, et al. Col. 32, line 64 to Col. 33, lines 1-5: "…map generation system (102) and/or vehicle computing system (106) determines one or more exit locations of the global route at a predetermined distance (e.g., at a threshold distance from the starting location, at a threshold distance from a current location of autonomous vehicle (104), etc.) [based on current location of autonomous vehicle and destination location." ; Dean, et al. Col. 33, lines 47-51: "…determines a plurality of candidate local routes, in the one or more roadways, for each exit location of the one or more exit locations [generates routes].")
and determine costs for the generated routes by adding an additional cost to each of the generated routes which pass within a radial distance of any of the identified geographic locations for routes of the set of routes, (Dean, et al. Col. 33, lines 5-9: "…map generation system (102) and/or vehicle computing system (106) may determine one or more exit locations in a cost field associated with a global route [identified geographic locations for routes based in set of routes] based on a sensor horizon (e.g., within a threshold distance of a sensor horizon) [pass though radial distance]." ; Dean, et al. Step (808), Fig. 8, Col 46, lines 9-18: "…adjusting costs of local routes associated with the global route to the destination location and determining local routes or roadways that satisfy one or more threshold costs for the coverage route [adding costs to created routes].")
and wherein determining whether to use the selected route or a new route is based on the determined costs (Dean, et al. Col. 34, lines 33-42: "…determines one or more diversion points based on determining a change in lane identifier associated with a lower cost route on the forks [judgment made based on determined costs]. For example, a change in lane identifier along with a lower cost route extending from a diversion point (e.g., a fork in route, etc.) may refer to a diversion point in the local graph where the route diverges (e.g., forks, splits, etc.) from a single route into at least two routes [selection of existing route or new route]").
Regarding claim 17, Dean, et al. and Kundu, et al. remain as applied to claim 10, and in a further embodiment, teaches: The system of claim 10, wherein the trip plan further identifies a plurality of geographic locations for each given route of the set of routes which when connected together with a pickup location and the destination location correspond to the given route, and the one or more processors are further configured to: (Dean, et al. Col. 28, lines 37-47: "…a plurality of local routes (e.g., a route option in a global cost field, a portion of a global route, an alternative to a global route, etc.) in one or more roadways between a starting location of autonomous vehicle (104) (e.g., a current location of autonomous vehicle (104), etc.) and a plurality of exit locations that are located between a starting location of the AV and a destination location of the AV [plurality of geographic locations are connected between pickup and destination location for route]." ; Dean, et al. Col. 27, lines 17-21: "…a global route associated with each route of a plurality of routes [each route in the set of routes] in a geographic location between a starting location and a destination location.")
generate routes based on a current location of the autonomous vehicle and the destination location; (Dean, et al. Col. 32, line 64 to Col. 33, lines 1-5: "…map generation system (102) and/or vehicle computing system (106) determines one or more exit locations of the global route at a predetermined distance (e.g., at a threshold distance from the starting location, at a threshold distance from a current location of autonomous vehicle (104), etc.) [based on current location of autonomous vehicle and destination location." ; Dean, et al. Col. 33, lines 47-51: "…determines a plurality of candidate local routes, in the one or more roadways, for each exit location of the one or more exit locations [generates routes].")
and determine costs for the generated routes by adding an additional cost to each of the generated routes which pass within a radial distance of any of the identified geographic locations for routes of the set of routes other than the selected route, (Dean, et al. Col. 33, lines 5-9: "…map generation system (102) and/or vehicle computing system (106) may determine one or more exit locations in a cost field associated with a global route [identified geographic locations for routes based in set of routes] based on a sensor horizon (e.g., within a threshold distance of a sensor horizon) [pass though radial distance]." ; Dean, et al. Col. 34, lines 45-48: "…lower cost paths on the forks provides efficiency and accuracy by eliminating creation of any diversion point where a new path includes a higher cost than a current path [adding additional cost to routes that pass through routes other than selected route; filters out these routes].")
and wherein determining whether to use the selected route or a new route is based on the determined costs (Dean, et al. Col. 34, lines 33-42: "…determines one or more diversion points based on determining a change in lane identifier associated with a lower cost route on the forks [judgment made based on determined costs]. For example, a change in lane identifier along with a lower cost route extending from a diversion point (e.g., a fork in route, etc.) may refer to a diversion point in the local graph where the route diverges (e.g., forks, splits, etc.) from a single route into at least two routes [selection of existing route or new route]").
Regarding claim 19, Dean, et al. and Kundu, et al. remains as applied to claim 10, and in a further embodiment, teaches: The system of claim 10, further comprising the autonomous vehicle (Fig. 1, Dean, et al. Col. 17, lines 35-37: "…map generation system (102) [system], autonomous vehicle (104) [autonomous vehicle]").
Regarding claim 20, Dean, et al. and Kundu, et al. remains as applied to claim 19, and in a further embodiment, teaches: The system of claim 19, further comprising, one or more server computing devices including one or more processors configured to send the dispatching instructions to the one or more processors, and wherein the one or more processors are part of the autonomous vehicle (Dean, et al. Col. 18, lines 21-24: "…autonomous vehicle (104) and/or vehicle computing system (106) includes one or more devices capable of receiving map data associated with a map of a geographic location [dispatching instructions]" ; Dean, et al. Col. 18, lines 36-39: "…autonomous vehicle (104) [autonomous vehicle] […] one or more processors (e.g., one or more servers [servers], etc.) [processors].").
Claims 9 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Dean, et al. (U.S. Patent No. 11333503) and Kundu, et al. (U.S. Patent Application Publication No. 20230080281) in view of Nagy, et al. (U.S. Patent No. 11441913).
Regarding claim 9, the combination of Dean, et al. and Kundu, et al. teaches: The method of claim 1, wherein the trip plan further identifies a geographic location between a pickup location and the destination location on the selected route, (Dean, et al. Step (502), Fig. 5, Col. 32, lines 61-66: "…includes determining one or more exit locations based on a threshold distance and the current location of the AV [identifies geographic location between pickup location and destination location on route]")
and the method further comprises: generating routes based on a current location of the autonomous vehicle and the destination location; (Dean, et al. Step (502), Fig. 5, Col. 32, lines 61-63: "…determining one or more exit locations based on a threshold distance and the current location of the AV [based on current location of autonomous vehicle and destination location]." ; Dean, et al. Step (504), Col. 33, lines 44-51: "…determines a plurality of candidate local routes, in the one or more roadways, for each exit location of the one or more exit locations [generates routes]")
and wherein determining whether to use the selected route or a new route is based on the determined costs (Dean, et al. Col. 34, lines 33-42: "…determines one or more diversion points based on determining a change in lane identifier associated with a lower cost route on the forks [judgment made based on determined costs]. For example, a change in lane identifier along with a lower cost route extending from a diversion point (e.g., a fork in route, etc.) may refer to a diversion point in the local graph where the route diverges (e.g., forks, splits, etc.) from a single route into at least two routes [selection of existing route or new route]").
The combination of Dean, et al. and Kundu, et al. does not teach and determining costs for the generated routes by adding a negative cost to each of the generated routes which pass through the identified geographic location.
In a similar field of endeavor (autonomous vehicle waypoint routing), Nagy, et al. teaches: and determining costs for the generated routes by adding a negative cost to each of the generated routes which pass through the identified geographic location (Operation (404), Fig. 4, Col. 14, lines 58-61: "…cost for traversing to any given candidate vehicle start point can be more favorable (e.g., lower cost or higher reward) [negative cost] for candidate vehicle starting points that are closer, more accessible, or otherwise more favorable for picking-up the passenger [identified geographic location].").
Therefore, it would have been obvious to one of the ordinary skill of the art before the effective filing date of the claimed invention to modify the combination of Dean, et al. and Kundu, et al. to include the teaching of Nagy, et al. based on a reasonable expectation of success and motivation to improve routing of an autonomous vehicle (Nagy, et al. Col. 2, lines 51-62).
Regarding claim 18, the combination of Dean, et al. and Kundu, et al. teaches: The system of claim 10, wherein the trip plan further identifies a geographic location between a pickup location and the destination location on the selected route, and the one or more processors are further configured to: (Dean, et al. Col. 32, line 64 to Col. 33, lines 1-5: "…map generation system (102) and/or vehicle computing system (106) determines one or more exit locations of the global route at a predetermined distance (e.g., at a threshold distance from the starting location, at a threshold distance from a current location of autonomous vehicle (104), etc.) [identifies geographic location between pickup location and destination location on route].")
generate routes based on a current location of the autonomous vehicle and the destination location; (Dean, et al. Col. 32, line 64 to Col. 33, lines 1-5: "…map generation system (102) and/or vehicle computing system (106) determines one or more exit locations of the global route at a predetermined distance (e.g., at a threshold distance from the starting location, at a threshold distance from a current location of autonomous vehicle (104), etc.) [based on current location of autonomous vehicle and destination location." ; Dean, et al. Col. 33, lines 47-51: "…determines a plurality of candidate local routes, in the one or more roadways, for each exit location of the one or more exit locations [generates routes].")
and wherein determining whether to use the selected route or a new route is based on the determined costs (Dean, et al. Col. 34, lines 33-42: "…determines one or more diversion points based on determining a change in lane identifier associated with a lower cost route on the forks [judgment made based on determined costs]. For example, a change in lane identifier along with a lower cost route extending from a diversion point (e.g., a fork in route, etc.) may refer to a diversion point in the local graph where the route diverges (e.g., forks, splits, etc.) from a single route into at least two routes [selection of existing route or new route]").
The combination of Dean, et al. and Kundu, et al. does not teach and determining costs for the generated routes by adding a negative cost to each of the generated routes which pass through the identified geographic location.
In a similar field of endeavor (autonomous vehicle waypoint routing), Nagy, et al. teaches: and determine costs for the generated routes by adding a negative cost to each of the generated routes which pass through the identified geographic location (Col. 14, lines 58-61: "…cost for traversing to any given candidate vehicle start point can be more favorable (e.g., lower cost or higher reward) [negative cost] for candidate vehicle starting points that are closer, more accessible, or otherwise more favorable for picking-up the passenger [identified geographic location].").
Therefore, it would have been obvious to one of the ordinary skill of the art before the effective filing date of the claimed invention to modify the combination of Dean, et al. and Kundu, et al. to include the teaching of Nagy, et al. based on a reasonable expectation of success and motivation to improve routing of an autonomous vehicle (Nagy, et al. Col. 2, lines 51-62).
Claims 21-22 are rejected under 35 U.S.C. 103 as being unpatentable over Dean, et al. (U.S. Patent No. 11333503) and Kundu, et al. (U.S. Patent Application Publication No. 20230080281) in view of Bonanni, et al. (U.S. Patent No. 11898859).
Regarding claim 21, the combination of Dean, et al. and Kundu, et al. does not teach the system of claim 10, wherein enforcing the trip plan includes: enforce, during the control of the autonomous vehicle to the destination location, the trip plan based on differences between a cost of the selected route and costs of unselected routes to the destination location from a current location of the autonomous vehicle including at least one of: a cost difference between a cost of the selected route and a cost of an optimal route of the set of two or more routes; an additional cost added to routes that pass through or come within a radial distance around at least one location on each unselected route of the set of two or more routes that is not the destination location or a current location; or a discount cost added to routes that pass through or come within a radial distance around at least one location on the selected route that is not the destination location or a current location.
In a similar field of endeavor (updating routing data), Bonanni, et al. teaches: The system of claim 10, wherein enforcing the trip plan includes: enforce, during the control of the autonomous vehicle to the destination location, the trip plan based on differences between a cost of the selected route and costs of unselected routes to the destination location from a current location of the autonomous vehicle including at least one of: a cost difference between a cost of the selected route and a cost of an optimal route of the set of two or more routes; an additional cost added to routes that pass through or come within a ra