DETAILED ACTION
Response to Amendments
This office action regarding application number 18/357,084, filed July 21, 2023, is in response to the applicants arguments and amendments filed December 30, 2025. Claim 13, 20, and 27 have been amended. Claims 13-32 are currently pending and are addressed below.
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 .
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 12/30/2025 has been entered.
Information Disclosure Statement
The information disclosure statement filed on 2/11/2026 is being considered by the examiner.
Response to Arguments
The applicants arguments and amendments to the application have overcome some of the objections and rejections previously set forth in the Final action mailed September 30, 2025. Applicants amendments to claim 13, 20 and 27 have been deemed sufficient to overcome the previous 35 USC 102 rejection through the inclusion of “wherein the goal region is expanded according to the passenger input and the expanded goal region is searched to determine updated feasible stopping places”, therefore the rejections are withdrawn. However as this changes the scope of the claims, new art rejections have been made based on the changes in scope. Applicants amendments to the specification have overcome the previous drawing and specification objections, therefore the objections are withdrawn.
Applicant’s arguments with respect to claim(s) 13, 20 and 27 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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 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.
Claim 13-17, 20-24, and 27-31 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rander (US-20170344010) in view of Cassandras (US-20140149153)
Regarding claim 13, Rander teaches a computer implemented method comprising (Paragraph [0018], "One or more examples described herein provide that methods, techniques, and actions performed by a computing device are performed programmatically, or as a computer-implemented method.")
obtaining a goal position from a passenger to be dropped off at a stopping place by a vehicle (Paragraph [0063], "In some examples, the transport directive 113 can include a pick-up location specified by the requesting user (302). Additionally, the transport directive 113 can include an inputted destination by the requesting user (304)," here the system is receiving a destination and pickup location from a user)
by at least one processor (Paragraph [0021], "Furthermore, one or more examples described herein may be implemented through the use of instructions that are executable by one or more processors.")
determining, by the at least one processor, a first acceptable stopping place in a goal region based on the goal position obtained from the passenger (Paragraph [0012], "When receiving “a pick-up location” from the requesting user, the transport facilitation system and/or the selected SDV itself can expand the inputted location to a “pick-up area” (e.g., a radius of twenty or forty meters for the inputted location pin) in order to generate a set of pick-up location options for an SDV selected to service the pick-up request," here after receiving a pick up location from a user the system will expand the location into a pick up area/goal region to generate a set of pick up locations/stopping places) (Paragraph [0057], "According to some examples, the drop-off of the requesting user can be performed in a similar manner," here the processing for pick up locations and drop off location can be performed in the same manner)
wherein one or more feasible stopping places are identified from map data associated with the goal region (Paragraph [0035], "In various implementations, the control system 120 can include a database 170 that stores operational sub-maps 172 for the given region," here the system includes a map data database including sub maps for a given region) (Paragraph [0044], "Furthermore, the database 170 of the SDV 100 can store pick-up and drop-off location sets 174 (PDOLS 174) for specified location areas ... Thus, if a requesting user inputs a pick-up location into a pick-up request 178—which may be indicated in the transport directive 113—the rendezvous logic 185 can expand the pick-up location into a pick-up area, and perform a lookup in the PDOLS 174 to identify a set of pick-up location options, or an options set 177, to rendezvous with the requesting user," here the map database includes stopping locations for a specified area, and once a user inputs a pick up or drop off location that information is used with the map database to identify pick up location options/stopping places)
obtaining, by the at least one processor, data representing perceptions of conditions at the goal region from at least one sensor of the vehicle (Paragraph [0035], "Accordingly, the control system 120 can dynamically analyze the real-time sensor data 111 from the sensors 101, 103 of the SDV 100 in view of a current sub-map 171 in order to dynamically determine its location and orientation within the given region, and detect and resolve any potential hazards to maneuver the SDV 100 and avoid such hazards if necessary," here the system obtains sensor/perception data of an area around the vehicle including a goal region)
updating, by the at least one processor, data indicative of the one or more feasible stopping places based on passenger input to include one or more updated feasible stopping places (Paragraph [0044], “In various implementations, the control system 120 can expand the pick-up location into a pick-up area with a certain radius (e.g., forty meters) from the inputted pick-up location by the requesting user. Furthermore, the database 170 of the SDV 100 can store pick-up and drop-off location sets 174 (PDOLS 174) for specified location areas.,” here the system is receiving a passenger input indicating a pickup/dropoff location, the system is then updating the feasible stopping places based on this input using a radius from the passenger input)
exposing, by the at least one processor, the updated data to a planning process that selects an updated acceptable stopping place for the vehicle from among the one or more updated feasible stopping places (Paragraph [0072], “Thus, if none of the location options in the options set 177 is available, and the traffic is below the threshold, the control system 120 can stop the SDV 100 at a current location, or at a location most proximate to the requesting user, to make the pick-up. However, if none of the location options are available and the traffic is above the threshold, then the control system 120 can perform a reserve operation to make the pick-up, as described herein. Such a reserve operation may include stopping in a red zone, double parking, or transmitting an update to the requesting user or backend transport facilitation system 190 indicating that the SDV 100 will loop around to make a second attempt.”)
and causing, by the at least one processor, the vehicle to drive to the updated acceptable stopping place (Paragraph [0027], "For example, the control system 120 can operate the vehicle 100 by autonomously steering, accelerating, and braking the vehicle 100 as the vehicle progresses to a destination.").
However Rander does not explicitly teach wherein the goal region is expanded according to the passenger input and the expanded goal region is searched to determine updated feasible stopping places.
Cassandras teaches a "smart parking" system and method for an urban environment based on a dynamic resource allocation including
wherein the goal region is expanded according to the passenger input and the expanded goal region is searched to determine updated feasible stopping places (Paragraph [0080], “Users may change their preferences or requirements at any time, including at any time after submitting a request. For example, during periods of limited resources or because the user's preferences are overly restrictive or if he/she fails to accept an offered resource, he/she will have to wait until the next decision point. During intervals between allocation decisions, users with no parking assignment have the opportunity to change their cost preference or their walking-distance requirements, possibly to increase the chance to be allocated. Because each user establishes his/her own preferences, it is, of course, possible that no parking space is ever assigned to a particular user,” here the system is using a user input/preferences in order to adjust search parameters for parking/stopping places, in this case, after the initial user input the system gives the user the option to adjust preferences including walking-distance requirements which expand the goal region, this system of changing preferences based on user input could reasonably be combined with the pickup/dropoff searching of Rander to expand a search area based on user input).
Rander and Cassandras are analogous art as they are both generally related to systems and methods for determining parking locations for vehicles.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include wherein the goal region is expanded according to the passenger input and the expanded goal region is searched to determine updated feasible stopping places of Cassandras in the systems and methods for selecting a stopping place for a vehicle of Rander with a reasonable expectation of success in order to improve the user experience by allowing them to change their preferences in order to improve the users chances of finding a stopping location (Paragraph [0016], “During intervals between allocation decisions made by the allocation center, users with no parking assignment may change their cost or walking-distance requirements sua sponte or may be prompted by the system to change their preference information, to improve the user's chances of an allocation if the system is highly utilized.”).
Regarding claim 14, the combination of Rander and Cassandras teaches the method as discussed above in claim 13, Rander further teaches comprising determining one or more potential stopping places for a vehicle within a region based on the goal position (Paragraph [0012], "When receiving “a pick-up location” from the requesting user, the transport facilitation system and/or the selected SDV itself can expand the inputted location to a “pick-up area” (e.g., a radius of twenty or forty meters for the inputted location pin) in order to generate a set of pick-up location options for an SDV selected to service the pick-up request," here after receiving a pick up location/goal position from a user the system will expand the location into a pick up area/goal region to generate a set of pick up locations/stopping places) (Paragraph [0057], "According to some examples, the drop-off of the requesting user can be performed in a similar manner," here the processing for pick up locations and drop off location can be performed in the same manner).
Regarding claim 15, the combination of Rander and Cassandras teaches the method as discussed above in claim 13, Rander further teaches wherein the goal position is obtained from the passenger via a touch based user interface, a mobile application, a kiosk, a notebook, a tablet, a workstation, or any combinations thereof (Paragraph [0020], “For example, one or more examples described herein may be implemented, in whole or in part, on computing devices such as servers, desktop computers, cellular or smartphones, personal digital assistants (e.g., PDAs), laptop computers, network equipment (e.g., routers), and tablet devices.”).
Regarding claim 16, the combination of Rander and Cassandras teaches the method as discussed above in claim 13, Rander further teaches comprising prompting the passenger to select the updated acceptable stopping place via a touch based user interface (Paragraph [0054], “In one variation, the rendezvous logic 185 can present the user device 175 with a plurality of available options (e.g., on a mapping feature), and the requesting user can select a particular option from the plurality. The rendezvous logic 185 can then instruct the vehicle control 128 to drive the SDV 100 to the selected location”).
Regarding claim 17, the combination of Rander and Cassandras teaches the method as discussed above in claim 13, Rander further teaches comprising prompting the passenger to select the updated acceptable stopping place via a voice command (Paragraph [0054], “In one variation, the rendezvous logic 185 can present the user device 175 with a plurality of available options (e.g., on a mapping feature), and the requesting user can select a particular option from the plurality. The rendezvous logic 185 can then instruct the vehicle control 128 to drive the SDV 100 to the selected location,” here the system can present a user with a plurality of options for a user to select) (Paragraph [0058], “In certain implementations, the control system 120 of the SDV 100 can enable the user to have at least partial control over the drop-off. For example, during the ride, the control system 120 can execute speech recognition to translate the user's spoken words into control commands. The translated commands can cause the control system 120 to operate various controllable parameters of the SDV 100 itself. For example, the spoken words of the user can be translated to control the climate control system, the audio and/or display system, certain network services (e.g., phoning, conferencing, content access, gaming, etc.), seat adjustment, and the like. According to examples described herein, the control system 120 can also operate the acceleration, braking, and steering system of the SDV 100 based on certain speech commands from the user. In one aspect, as the SDV 100 approaches the destination, the user can ask or otherwise command the SDV 100 to stop at its current location,” here the system can recognize a users voice command as an input such as the selection of the earlier presented options).
Regarding claim 20, Rander teaches a system comprising (Paragraph [0010], “A self-driving car (SDV) is disclosed that can optimize pick-ups with requesting users. The SDV can communicate with a backend transport facilitation system that manages a transportation arrangement service for users throughout a given region.”)
at least one processor (Paragraph [0021], "Furthermore, one or more examples described herein may be implemented through the use of instructions that are executable by one or more processors.")
and at least one non-transitory storage media storing instructions that, when executed by the at least one processor cause the at least one processor to (Paragraph [0021], “Furthermore, one or more examples described herein may be implemented through the use of instructions that are executable by one or more processors. These instructions may be carried on a computer-readable medium.”)
obtain a goal position from a passenger to be dropped off at a stopping place by a vehicle (Paragraph [0063], "In some examples, the transport directive 113 can include a pick-up location specified by the requesting user (302). Additionally, the transport directive 113 can include an inputted destination by the requesting user (304)," here the system is receiving a destination and pickup location from a user)
determine, a first acceptable stopping place in a goal region based on the goal position obtained from the passenger (Paragraph [0012], "When receiving “a pick-up location” from the requesting user, the transport facilitation system and/or the selected SDV itself can expand the inputted location to a “pick-up area” (e.g., a radius of twenty or forty meters for the inputted location pin) in order to generate a set of pick-up location options for an SDV selected to service the pick-up request," here after receiving a pick up location from a user the system will expand the location into a pick up area/goal region to generate a set of pick up locations/stopping places) (Paragraph [0057], "According to some examples, the drop-off of the requesting user can be performed in a similar manner," here the processing for pick up locations and drop off location can be performed in the same manner)
wherein one or more feasible stopping places are identified from map data associated with the goal region (Paragraph [0035], "In various implementations, the control system 120 can include a database 170 that stores operational sub-maps 172 for the given region," here the system includes a map data database including sub maps for a given region) (Paragraph [0044], "Furthermore, the database 170 of the SDV 100 can store pick-up and drop-off location sets 174 (PDOLS 174) for specified location areas ... Thus, if a requesting user inputs a pick-up location into a pick-up request 178—which may be indicated in the transport directive 113—the rendezvous logic 185 can expand the pick-up location into a pick-up area, and perform a lookup in the PDOLS 174 to identify a set of pick-up location options, or an options set 177, to rendezvous with the requesting user," here the map database includes stopping locations for a specified area, and once a user inputs a pick up or drop off location that information is used with the map database to identify pick up location options/stopping places)
obtain data representing perceptions of conditions at the goal region from at least one sensor of the vehicle (Paragraph [0035], "Accordingly, the control system 120 can dynamically analyze the real-time sensor data 111 from the sensors 101, 103 of the SDV 100 in view of a current sub-map 171 in order to dynamically determine its location and orientation within the given region, and detect and resolve any potential hazards to maneuver the SDV 100 and avoid such hazards if necessary," here the system obtains sensor/perception data of an area around the vehicle including a goal region)
update data indicative of the one or more feasible stopping places based on passenger input to include one or more updated feasible stopping places (Paragraph [0044], “In various implementations, the control system 120 can expand the pick-up location into a pick-up area with a certain radius (e.g., forty meters) from the inputted pick-up location by the requesting user. Furthermore, the database 170 of the SDV 100 can store pick-up and drop-off location sets 174 (PDOLS 174) for specified location areas.,” here the system is receiving a passenger input indicating a pickup/dropoff location, the system is then updating the feasible stopping places based on this input using a radius from the passenger input)
expose the updated data to a planning process that selects an updated acceptable stopping place for the vehicle from among the one or more updated feasible stopping places (Paragraph [0072], “Thus, if none of the location options in the options set 177 is available, and the traffic is below the threshold, the control system 120 can stop the SDV 100 at a current location, or at a location most proximate to the requesting user, to make the pick-up. However, if none of the location options are available and the traffic is above the threshold, then the control system 120 can perform a reserve operation to make the pick-up, as described herein. Such a reserve operation may include stopping in a red zone, double parking, or transmitting an update to the requesting user or backend transport facilitation system 190 indicating that the SDV 100 will loop around to make a second attempt.”)
and cause the vehicle to navigate to the updated acceptable stopping place (Paragraph [0027], "For example, the control system 120 can operate the vehicle 100 by autonomously steering, accelerating, and braking the vehicle 100 as the vehicle progresses to a destination.").
However Rander does not explicitly teach wherein the goal region is expanded according to the passenger input and the expanded goal region is searched to determine updated feasible stopping places.
Cassandras teaches a "smart parking" system and method for an urban environment based on a dynamic resource allocation including
wherein the goal region is expanded according to the passenger input and the expanded goal region is searched to determine updated feasible stopping places (Paragraph [0080], “Users may change their preferences or requirements at any time, including at any time after submitting a request. For example, during periods of limited resources or because the user's preferences are overly restrictive or if he/she fails to accept an offered resource, he/she will have to wait until the next decision point. During intervals between allocation decisions, users with no parking assignment have the opportunity to change their cost preference or their walking-distance requirements, possibly to increase the chance to be allocated. Because each user establishes his/her own preferences, it is, of course, possible that no parking space is ever assigned to a particular user,” here the system is using a user input/preferences in order to adjust search parameters for parking/stopping places, in this case, after the initial user input the system gives the user the option to adjust preferences including walking-distance requirements which expand the goal region, this system of changing preferences based on user input could reasonably be combined with the pickup/dropoff searching of Rander to expand a search area based on user input).
Rander and Cassandras are analogous art as they are both generally related to systems and methods for determining parking locations for vehicles.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include wherein the goal region is expanded according to the passenger input and the expanded goal region is searched to determine updated feasible stopping places of Cassandras in the systems and methods for selecting a stopping place for a vehicle of Rander with a reasonable expectation of success in order to improve the user experience by allowing them to change their preferences in order to improve the users chances of finding a stopping location (Paragraph [0016], “During intervals between allocation decisions made by the allocation center, users with no parking assignment may change their cost or walking-distance requirements sua sponte or may be prompted by the system to change their preference information, to improve the user's chances of an allocation if the system is highly utilized.”).
Regarding claim 21, claim 21 is similar in scope to claim 14 and therefore is rejected under similar rationale.
Regarding claim 22, claim 22 is similar in scope to claim 15 and therefore is rejected under similar rationale.
Regarding claim 23, claim 23 is similar in scope to claim 16 and therefore is rejected under similar rationale.
Regarding claim 24, claim 24 is similar in scope to claim 17 and therefore is rejected under similar rationale.
Regarding claim 27, Rander teaches a system, comprising: at least one processor, and at least one non-transitory storage media storing instructions that, when executed by the at least one processor, cause the at least one processor to: (Paragraph [0021], "Furthermore, one or more examples described herein may be implemented through the use of instructions that are executable by one or more processors.") (Paragraph [0021], “Furthermore, one or more examples described herein may be implemented through the use of instructions that are executable by one or more processors. These instructions may be carried on a computer-readable medium.”)
obtain a goal position from a passenger to be dropped off at a stopping place by a vehicle (Paragraph [0063], "In some examples, the transport directive 113 can include a pick-up location specified by the requesting user (302). Additionally, the transport directive 113 can include an inputted destination by the requesting user (304)," here the system is receiving a destination and pickup location from a user)
determine, a first acceptable stopping place in a goal region based on the goal position obtained from the passenger (Paragraph [0012], "When receiving “a pick-up location” from the requesting user, the transport facilitation system and/or the selected SDV itself can expand the inputted location to a “pick-up area” (e.g., a radius of twenty or forty meters for the inputted location pin) in order to generate a set of pick-up location options for an SDV selected to service the pick-up request," here after receiving a pick up location from a user the system will expand the location into a pick up area/goal region to generate a set of pick up locations/stopping places) (Paragraph [0057], "According to some examples, the drop-off of the requesting user can be performed in a similar manner," here the processing for pick up locations and drop off location can be performed in the same manner)
wherein one or more feasible stopping places are identified from map data associated with the goal region (Paragraph [0035], "In various implementations, the control system 120 can include a database 170 that stores operational sub-maps 172 for the given region," here the system includes a map data database including sub maps for a given region) (Paragraph [0044], "Furthermore, the database 170 of the SDV 100 can store pick-up and drop-off location sets 174 (PDOLS 174) for specified location areas ... Thus, if a requesting user inputs a pick-up location into a pick-up request 178—which may be indicated in the transport directive 113—the rendezvous logic 185 can expand the pick-up location into a pick-up area, and perform a lookup in the PDOLS 174 to identify a set of pick-up location options, or an options set 177, to rendezvous with the requesting user," here the map database includes stopping locations for a specified area, and once a user inputs a pick up or drop off location that information is used with the map database to identify pick up location options/stopping places)
obtain data representing perceptions of conditions at the goal region from at least one sensor of the vehicle (Paragraph [0035], "Accordingly, the control system 120 can dynamically analyze the real-time sensor data 111 from the sensors 101, 103 of the SDV 100 in view of a current sub-map 171 in order to dynamically determine its location and orientation within the given region, and detect and resolve any potential hazards to maneuver the SDV 100 and avoid such hazards if necessary," here the system obtains sensor/perception data of an area around the vehicle including a goal region)
update data indicative of the one or more feasible stopping places based on passenger input to include one or more updated feasible stopping places (Paragraph [0044], “In various implementations, the control system 120 can expand the pick-up location into a pick-up area with a certain radius (e.g., forty meters) from the inputted pick-up location by the requesting user. Furthermore, the database 170 of the SDV 100 can store pick-up and drop-off location sets 174 (PDOLS 174) for specified location areas.,” here the system is receiving a passenger input indicating a pickup/dropoff location, the system is then updating the feasible stopping places based on this input using a radius from the passenger input)
expose the updated data to a planning process that selects an updated acceptable stopping place for the vehicle from among the one or more updated feasible stopping places (Paragraph [0072], “Thus, if none of the location options in the options set 177 is available, and the traffic is below the threshold, the control system 120 can stop the SDV 100 at a current location, or at a location most proximate to the requesting user, to make the pick-up. However, if none of the location options are available and the traffic is above the threshold, then the control system 120 can perform a reserve operation to make the pick-up, as described herein. Such a reserve operation may include stopping in a red zone, double parking, or transmitting an update to the requesting user or backend transport facilitation system 190 indicating that the SDV 100 will loop around to make a second attempt.”)
and cause the vehicle to navigate to the updated acceptable stopping place (Paragraph [0027], "For example, the control system 120 can operate the vehicle 100 by autonomously steering, accelerating, and braking the vehicle 100 as the vehicle progresses to a destination.").
However Rander does not explicitly teach wherein the goal region is expanded according to the passenger input and the expanded goal region is searched to determine updated feasible stopping places.
Cassandras teaches a "smart parking" system and method for an urban environment based on a dynamic resource allocation including
wherein the goal region is expanded according to the passenger input and the expanded goal region is searched to determine updated feasible stopping places (Paragraph [0080], “Users may change their preferences or requirements at any time, including at any time after submitting a request. For example, during periods of limited resources or because the user's preferences are overly restrictive or if he/she fails to accept an offered resource, he/she will have to wait until the next decision point. During intervals between allocation decisions, users with no parking assignment have the opportunity to change their cost preference or their walking-distance requirements, possibly to increase the chance to be allocated. Because each user establishes his/her own preferences, it is, of course, possible that no parking space is ever assigned to a particular user,” here the system is using a user input/preferences in order to adjust search parameters for parking/stopping places, in this case, after the initial user input the system gives the user the option to adjust preferences including walking-distance requirements which expand the goal region, this system of changing preferences based on user input could reasonably be combined with the pickup/dropoff searching of Rander to expand a search area based on user input).
Rander and Cassandras are analogous art as they are both generally related to systems and methods for determining parking locations for vehicles.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include wherein the goal region is expanded according to the passenger input and the expanded goal region is searched to determine updated feasible stopping places of Cassandras in the systems and methods for selecting a stopping place for a vehicle of Rander with a reasonable expectation of success in order to improve the user experience by allowing them to change their preferences in order to improve the users chances of finding a stopping location (Paragraph [0016], “During intervals between allocation decisions made by the allocation center, users with no parking assignment may change their cost or walking-distance requirements sua sponte or may be prompted by the system to change their preference information, to improve the user's chances of an allocation if the system is highly utilized.”).
Regarding claim 28, claim 28 is similar in scope to claim 14 and therefore is rejected under similar rationale.
Regarding claim 29, claim 29 is similar in scope to claim 15 and therefore is rejected under similar rationale.
Regarding claim 30, claim 30 is similar in scope to claim 16 and therefore is rejected under similar rationale.
Regarding claim 31, claim 31 is similar in scope to claim 17 and therefore is rejected under similar rationale.
Claim 18, 25, and 32 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rander (US-20170344010) in view of Cassandras (US-20140149153) and further in view of Benenson (US-20160061618).
Regarding claim 18, the combination of Rander and Cassandras teaches the method as discussed above in claim 13, Rander further teaches prompting the passenger to select the updated acceptable stopping place (Paragraph [0054], “In one variation, the rendezvous logic 185 can present the user device 175 with a plurality of available options (e.g., on a mapping feature), and the requesting user can select a particular option from the plurality. The rendezvous logic 185 can then instruct the vehicle control 128 to drive the SDV 100 to the selected location”).
However Rander does not explicitly teach automatically selects the updated acceptable stopping place in response to failing to make a selection within a specified time.
Benenson teaches systems and methods for determining a parking place for a vehicle including
automatically selects the updated acceptable stopping place in response to failing to make a selection within a specified time (Paragraph [0084-0085], “As discussed, a specific optimized parking route may be terminated when the driver finds a parking place (PP), or when the driver's decides to change the set of preferences or just to cancel the search and park on the parking lot. The latter may happen, for example, when the time budget goes to expire, so the driver (or the system) may cancel the best parking route and select a spare (additional) route parking which will navigate the user's vehicle to a paid parking lot close to the destination. Other examples may be found,” here the system in response to not receiving a driver input within a time budget, such as selecting a stopping place as taught by Rander, the system will take a default action and select an updated parking spot).
Rander, Cassandras, and Benenson are analogous art as they are both generally related to systems for determining a stopping place for a vehicle.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include automatically selects the updated acceptable stopping place in response to failing to make a selection within a specified time of Benenson in the system for selecting a stopping place of Rander and Cassandras with a reasonable expectation of success in order to improve the efficiency of the parking search by using preferences such as search time to limit a search (Paragraph [0200-0201], “The facility thus will be capable either to provide the user with a group of the most efficient parking routes, each satisfying a given set of criteria (parking preferences), or will be capable to report to the user that his/her preferences cannot be satisfied. Taken together, the group of alternative parking routes covers all best parking options in the area and makes the driver's parking search maximally efficient.”).
Regarding claim 25, claim 25 is similar in scope to claim 18 and therefore is rejected under similar rationale.
Regarding claim 32, claim 32 is similar in scope to claim 18 and therefore is rejected under similar rationale.
Claims 19 and 26 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rander (US-20170344010) in view of Cassandras (US-20140149153) and further in view of Herbach (US-20170057510).
Regarding claim 19, the combination of Rander and Cassandras teaches the method as discussed above in claim 13, Rander further teaches determine additional feasible stopping places in response to the vehicle failing to stop at the first acceptable stopping place or the updated acceptable stopping place (Paragraph [0056], “In further examples, the rendezvous logic 185 can determine that none of the pick-up location options are available. In such examples, the rendezvous logic 185 can rely more heavily on direct communications 187 with the user, and/or attempt to make the pick-up by utilizing a reserve option. Such reserve options can include double parking, stopping briefly in a yellow or red zone, taking a next turnout (e.g., into a side street or parking lot), etc. The rendezvous logic 185 can utilize the reserve options only when all other options are exhausted, or when the rendezvous logic 185 fails in a first attempt. Thus, in some examples, the rendezvous logic 185 can keep such reserve options locked, and unlock the reserve options based on one or more triggering events. Such triggering events can include the SDV 100 passing the inputted or actual location of the requesting user, a failed pick-up attempt and loop around action, detection of no available options, and the like. In certain examples, when reserve options are unlocked, the rendezvous logic 185 can transmit an alert to the user device 175 to be aware and ready for a quick pick-up.”).
However Rander does not explicitly teach expanding the goal region and searching the expanded goal region to determine additional feasible stopping places.
Herbach teaches methods and systems for determining instructions for pulling over an autonomous vehicle including
expanding the goal region and searching the expanded goal region to determine additional feasible stopping places (Paragraph [0017], “The autonomous vehicle, or a computing device associated with the autonomous vehicle, may monitor a road ahead in order to identify a region for pulling over the autonomous vehicle. For example, at a given moment, the autonomous vehicle may monitor a section of the road that it will be driving through over the next ten seconds or other period of time following the given moment. The autonomous vehicle may use a variety of methods to determine whether the section of the road (e.g., the identified region) is safe or otherwise suitable for pulling over the autonomous vehicle. If the autonomous vehicle determines that the section of the road is not safe or not otherwise suitable for pulling over the autonomous vehicle, the autonomous vehicle may continue driving along its normal path and monitor a different section of the road that is further ahead of the previous section,” here in response to a trigger condition, such as the trigger condition of Rander when the vehicle fails to stop at an initial stopping place, the system continues to search for a stopping place but in a section of road that is further along, therefore expanding to goal region).
Rander, Cassandras, and Herbach are analogous art as they are both generally related to systems for determining a stopping place of an autonomous vehicle.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include expanding the goal region and searching the expanded goal region to determine additional feasible stopping places of Herbach in the system for determining a stopping place in response to a request of Rander and Cassandras with a reasonable expectation of success in order to improve the safety of the system by iteratively determining the nearest safe place for the vehicle to pull over instead of limiting the vehicle to a only a small unsafe area (Paragraph [0016], “In general, the autonomous vehicle may be looking for a safe space on or alongside the road to pull over. Some roads, such as those on bridges or those with obstructions in their shoulder lanes, may not be suitable or safe for pulling over the autonomous vehicle. As such, the autonomous vehicle may ideally look for a continuous shoulder or region of a road that is free of obstacles and otherwise suitable for pulling over.”).
Regarding claim 26, claim 26 is similar in scope to claim 19 and therefore is rejected under similar rationale.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Zhu (US-20140136045) teaches searching for stopping places for a vehicle configured to use its sensors to determine potential parking spots, such as causing the vehicle to travel down a road and checking for painted lines along a street that indicate an open parking space. Kentley (US-20170248964) teaches a fleet of autonomous vehicles which are configured to transit from a first geographical region to a second geographical region including determining parking spots. Ross (US-9940651) teaches a transport arrangement system operates to receive a transport request from a user, and to make a selection of a vehicle type for the user based at least in part on a set of criteria associated with the transport request or user information.
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/CHRISTOPHER GEORGE FEES/Examiner, Art Unit 3662