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 .
This is the first office action on the merits and is responsive to the papers filed on 11/21/2024. Claims 1-20 are currently pending.
Information Disclosure Statement
1. The Information Disclosure Statement (IDS) submitted on 11/21/2024 has been considered by the Examiner.
Specification
2. The lengthy specification has not been checked to the extent necessary to determine the presence of all possible minor errors. Applicant’s cooperation is requested in correcting any errors of which applicant may become aware in the specification.
Claim Rejections - 35 USC § 103
3. 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.
4. 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.
5. 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.
6. Claims 1-5, 8-14, and 16-19 are rejected under 35 U.S.C. 103 as being unpatentable over Selvam (US 20200126417 A1) in view of Petroff (US 20170185087 A1).
7. Regarding Claim 1, Selvam teaches a method comprising: running, by one or more processors based on map information corresponding to a service area of a fleet of autonomous vehicles, a first portion of a simulation for the fleet of autonomous vehicles (Selvam: [0015] and [0039]);
Running, by the one or more processors based on the map information, a second portion of the simulation including introducing a problem condition related to scheduling and dispatching of the fleet of autonomous vehicles, the second portion of the simulation being subsequent to the first portion of the simulation (Selvam: [0040] Note that under the broadest reasonable interpretation, the problem condition is interpreted as vehicle maintenance/charging.);
Running, by the one or more processors based on the map information, a third portion of the simulation including a response of a scheduling system to the problem condition, the third portion of the simulation being subsequent to the second portion of the simulation (Selvam: [0040] and [0046]),
Wherein running the first portion, the second portion and the third portion of the simulation includes: controlling, by respective autonomous vehicle control of each autonomous vehicle of the fleet of autonomous vehicles… (Selvam: [0055]);
And simulating scheduling and dispatching of the fleet of autonomous vehicles by the scheduling system (Selvam: [0020] and [0055]);
And evaluating, by the one or more processors, one or more decisions by the scheduling system during at least the third portion of the simulation (Selvam: [0046]).
Selvam fails to explicitly teach controlling... the autonomous vehicle along at least a portion of a respective route to a respective destination.
However, in the same field of endeavor, Petroff teaches wherein running the first portion, the second portion and the third portion of the simulation includes: controlling, by respective autonomous vehicle control of each autonomous vehicle of the fleet of autonomous vehicles, the autonomous vehicle along at least a portion of a respective route to a respective destination (Petroff: [0028], [0029], and [0060]).
Selvam and Petroff are considered to be analogous to the claim invention because they are in the same field of autonomous vehicle simulation. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to modify Selvam to incorporate the teachings of Petroff to control the autonomous vehicle along a portion of the respective route by autonomous vehicle control of each autonomous vehicle because it provides the benefit of running an optimization simulation with problem condition scenarios. Petroff explains in [0025] that a reinforced learning simulation is required due to changing factors as vehicles traverse along the assigned route. Therefore, there is a major benefit to adjust the simulated situation based on road closures/openings and vehicle maintenance.
8. Regarding Claim 2, Selvam and Petroff remains as applied above in Claim 1, and further, Selvam teaches receiving, by the scheduling system, a notification of the problem condition from an autonomous vehicle of the fleet of autonomous vehicles (Selvam: [0034]).
9. Regarding Claim 3, Selvam and Petroff remains as applied above in Claim 2, and further, Selvam teaches the problem condition includes the autonomous vehicle going out of service during at least the second portion of the simulation (Selvam: [0034] and [0040]).
10. Regarding Claim 4, Selvam and Petroff remains as applied above in Claim 3, and further, Selvam teaches the problem condition further includes the autonomous vehicle encountering a component failure during at least the second portion of the simulation (Selvam: [0014] and [0040]).
11. Regarding Claim 5, Selvam and Petroff remains as applied above in Claim 3, and further, Petroff teaches the problem condition further includes the autonomous vehicle being in an accident during at least the second portion of the simulation (Petroff: [0028] and [0060]).
12. Regarding Claim 8, Selvam and Petroff remains as applied above in Claim 1, and further, Selvam teaches running the second portion of the simulation further includes receiving, by the scheduling system, a notification of the problem condition from a computing system separate from the scheduling system (Selvam: [0034]).
13. Regarding Claim 9, Selvam and Petroff remains as applied above in Claim 1, and further, Selvam teaches running the first portion, the second portion and the third portion of the simulation further includes picking up and dropping off, by one or more autonomous vehicles of the fleet of autonomous vehicles, users of a transportation service at different locations in the service area (Selvam: [0024], [0033], and [0054]).
14. Regarding Claim 10, Selvam and Petroff remains as applied above in Claim 1, and further, Selvam teaches determining, by the one or more processors, a score associated with the scheduling and dispatching of the fleet of autonomous vehicles by the scheduling system during at least the third portion of the simulation, wherein evaluating the one or more decisions by the scheduling system is based on the score (Selvam: [0040] Note that under the broadest reasonable interpretation, the score is equivalent to the variables (e.g., revenue).).
15. Regarding Claim 11, Selvam teaches a system comprising a simulation system including one or more computing devices configured to (Selvam: [0029]):
Run, based on map information corresponding to a service area of a fleet of autonomous vehicles, a first portion of a simulation of the fleet of autonomous vehicles (Selvam: [0015] and [0039]);
Run, based on the map information, a second portion of the simulation including introduction of a problem condition related to scheduling and dispatching of the fleet of autonomous vehicles, the second portion of the simulation being subsequent to the first portion of the simulation (Selvam: [0040] Note that under the broadest reasonable interpretation, the problem condition is interpreted as vehicle maintenance/charging.);
Run, based on the map information, a third portion of the simulation including a response of a scheduling system to the problem condition, the third portion of the simulation being subsequent to the second portion of the simulation (Selvam: [0040] and [0046]),
Wherein the first portion, the second portion and the third portion of the simulation includes: control of, by respective autonomous vehicle control of each autonomous vehicle of the fleet of autonomous vehicles… (Selvam: [0055]);
And simulation of scheduling and dispatching of the fleet of autonomous vehicles by the scheduling system (Selvam: [0020] and [0055]);
And evaluate one or more decisions by the scheduling system during at least the third portion of the simulation (Selvam: [0046]).
Selvam fails to explicitly teach control of... the autonomous vehicle along at least a portion of a respective route to a respective destination.
However, in the same field of endeavor, Petroff teaches wherein the first portion, the second portion and the third portion of the simulation includes: control of, by respective autonomous vehicle control of each autonomous vehicle of the fleet of autonomous vehicles, the autonomous vehicle along at least a portion of a respective route to a respective destination (Petroff: [0028], [0029], and [0060]).
Selvam and Petroff are considered to be analogous to the claim invention because they are in the same field of autonomous vehicle simulation. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to modify Selvam to incorporate the teachings of Petroff to control the autonomous vehicle along a portion of the respective route by autonomous vehicle control of each autonomous vehicle because it provides the benefit of running an optimization simulation with problem condition scenarios. Petroff explains in [0025] that a reinforced learning simulation is required due to changing factors as vehicles traverse along the assigned route. Therefore, there is a major benefit to adjust the simulated situation based on road closures/openings and vehicle maintenance.
16. Regarding Claim 12, Selvam and Petroff remains as applied above in Claim 11, and further, Selvam teaches the problem condition includes an autonomous vehicle of the fleet of autonomous vehicles encountering a hardware failure during at least the second portion of the simulation (Selvam: [0034] and [0049]),
And the second portion of the simulation includes notification of the problem condition from the autonomous vehicle to the scheduling system (Selvam: [0034]).
17. Regarding Claim 13, Selvam and Petroff remains as applied above in Claim 11, and further, Selvam teaches the problem condition includes an autonomous vehicle of the fleet of autonomous vehicles encountering a software failure during at least the second portion of the simulation (Selvam: [0034] and [0049]),
And the second portion of the simulation includes notification of the problem condition from the autonomous vehicle to the scheduling system (Selvam: [0034]).
18. Regarding Claim 14, Selvam and Petroff remains as applied above in Claim 11, and further, Petroff teaches the problem condition includes an autonomous vehicle of the fleet of autonomous vehicles being in an accident during at least the second portion of the simulation (Petroff: [0028] and [0060]),
And the second portion of the simulation includes notification of the problem condition from the autonomous vehicle to the scheduling system (Petroff: [0017] and [0067]).
19. Regarding Claim 16, Selvam and Petroff remains as applied above in Claim 11, and further, Selvam teaches the second portion of the simulation further includes notification of the problem condition from a transportation service to the scheduling system, the transportation service being hosted on a computing device separate from the scheduling system (Selvam: [0034]).
20. Regarding Claim 17, Selvam and Petroff remains as applied above in Claim 11, and further, Selvam teaches the one or more computing devices are configured to, during the first portion, the second portion and the third portion of the simulation, simulate picking up and dropping off, by one or more autonomous vehicles of the fleet of autonomous vehicles, users of a transportation service at different locations in the service area (Selvam: [0024], [0033], and [0054]).
21. Regarding Claim 18, Selvam teaches a non-transitory computer-readable medium on which instructions are stored, the instructions, when executed by one or more processors cause the one or more processors to perform a method comprising (Selvam: [0064] and [0071]):
Running, based on map information corresponding to a service area of a fleet of autonomous vehicles, a first portion of a simulation of the fleet of autonomous vehicles (Selvam: [0015] and [0039]);
Running, based on the map information, a second portion of the simulation including introduction of a problem condition related to scheduling and dispatching of the fleet of autonomous vehicles, the second portion of the simulation being subsequent to the first portion of the simulation (Selvam: [0040] Note that under the broadest reasonable interpretation, the problem condition is interpreted as vehicle maintenance/charging.);
Running, based on the map information, a third portion of the simulation including a response of a scheduling system to the problem condition, the third portion of the simulation being subsequent to the second portion of the simulation (Selvam: [0040] and [0046]),
Wherein running the first portion, the second portion and the third portion of the simulation includes: controlling, by respective autonomous vehicle control of each autonomous vehicle of the fleet of autonomous vehicles… (Selvam: [0055]);
And simulating scheduling and dispatching of the fleet of autonomous vehicles by the scheduling system (Selvam: [0020] and [0055]);
And evaluating one or more decisions by the scheduling system during at least the third portion of the simulation (Selvam: [0046]).
Selvam fails to explicitly teach controlling... the autonomous vehicle along at least a portion of a respective route to a respective destination.
However, in the same field of endeavor, Petroff teaches wherein running the first portion, the second portion and the third portion of the simulation includes: controlling, by respective autonomous vehicle control of each autonomous vehicle of the fleet of autonomous vehicles, the autonomous vehicle along at least a portion of a respective route to a respective destination (Petroff: [0028], [0029], and [0060]).
Selvam and Petroff are considered to be analogous to the claim invention because they are in the same field of autonomous vehicle simulation. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to modify Selvam to incorporate the teachings of Petroff to control the autonomous vehicle along a portion of the respective route by autonomous vehicle control of each autonomous vehicle because it provides the benefit of running an optimization simulation with problem condition scenarios. Petroff explains in [0025] that a reinforced learning simulation is required due to changing factors as vehicles traverse along the assigned route. Therefore, there is a major benefit to adjust the simulated situation based on road closures/openings and vehicle maintenance.
22. Regarding Claim 19, Selvam and Petroff remains as applied above in Claim 18, and further, Selvam teaches running the second portion of the simulation further includes receiving, by the scheduling system, a notification of the problem condition from an autonomous vehicle of the fleet of autonomous vehicles (Selvam: [0034]).
23. Claims 6-7, 15, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Selvam (US 20200126417 A1), in view of Petroff (US 20170185087 A1), and in further view of Zaytsev (US 20200409369 A1).
24. Regarding Claim 6, Selvam and Petroff remains as applied above in Claim 1.
Selvam and Petroff fail to explicitly teach running the second portion of the simulation further includes receiving, by the scheduling system, a notification of the problem condition from a user of a transportation service.
However, in the same field of endeavor, Zaytsev teaches running the second portion of the simulation further includes receiving, by the scheduling system, a notification of the problem condition from a user of a transportation service (Zaytsev: [0112]).
Selvam, Petroff, and Zaytsev are considered to be analogous to the claim invention because they are in the same field of autonomous vehicle simulation. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to modify Selvam and Petroff to incorporate the teachings of Zaytsev to provide a problem condition from a user of a transportation service because it provides the benefit of informing the scheduling system that a vehicle had an unexpected event and the rest of the schedule can be optimized based on the change in vehicle state. Receiving a notification from the user of the transportation service is advantageous because the simulation can determine a failure state as it happens and improve the response of the control of the failed vehicle and other vehicles in the fleet.
25. Regarding Claim 7, Selvam, Petroff, and Zaytsev remain as applied above in Claim 6, and further, Zaytsev teaches the problem condition includes a delay in the user meeting an autonomous vehicle of the fleet of autonomous vehicles during at least the second portion of the simulation (Zaytsev: [0032], [0043], and [0108]).
26. Regarding Claim 15, Selvam and Petroff remains as applied above in Claim 11.
Selvam and Petroff fail to explicitly teach the problem condition includes a delay in a user meeting an autonomous vehicle of the fleet of autonomous vehicles during at least the second portion of the simulation, and the second portion of the simulation includes notification of the problem condition from a transportation service to the scheduling system.
However, in the same field of endeavor, Zaytsev teaches the problem condition includes a delay in a user meeting an autonomous vehicle of the fleet of autonomous vehicles during at least the second portion of the simulation (Zaytsev: [0032], [0043], and [0108]),
And the second portion of the simulation includes notification of the problem condition from a transportation service to the scheduling system (Zaytsev: [0112]).
Selvam, Petroff, and Zaytsev are considered to be analogous to the claim invention because they are in the same field of autonomous vehicle simulation. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to modify Selvam and Petroff to incorporate the teachings of Zaytsev for the problem condition to include a delay and to provide a problem condition from a user of a transportation service because it provides the benefit of informing the scheduling system that a vehicle had an unexpected event and the rest of the schedule can be optimized based on the change in vehicle state. Receiving a notification from the user of the transportation service is advantageous because the simulation can determine a failure state as it happens and improve the response of the control of the failed vehicle and other vehicles in the fleet.
27. Regarding Claim 20, Selvam and Petroff remains as applied above in Claim 18.
Selvam and Petroff fail to explicitly teach running the second portion of the simulation further includes receiving, by the scheduling system, a notification of the problem condition from a user of a transportation service supported by the fleet of autonomous vehicles.
However, in the same field of endeavor, Zaytsev teaches running the second portion of the simulation further includes receiving, by the scheduling system, a notification of the problem condition from a user of a transportation service supported by the fleet of autonomous vehicles (Zaytsev: [0112]).
Selvam, Petroff, and Zaytsev are considered to be analogous to the claim invention because they are in the same field of autonomous vehicle simulation. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to modify Selvam and Petroff to incorporate the teachings of Zaytsev to provide a problem condition from a user of a transportation service because it provides the benefit of informing the scheduling system that a vehicle had an unexpected event and the rest of the schedule can be optimized based on the change in vehicle state. Receiving a notification from the user of the transportation service is advantageous because the simulation can determine a failure state as it happens and improve the response of the control of the failed vehicle and other vehicles in the fleet.
Conclusion
28. Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL T SILVA whose telephone number is (571)272-6506. The examiner can normally be reached Mon-Tues: 7AM - 4:30PM ET; Wed-Thurs: 7AM-6PM ET; Fri: OFF.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Angela Ortiz can be reached at 571-272-1206. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MICHAEL T SILVA/Examiner, Art Unit 3663
/ANGELA Y ORTIZ/Supervisory Patent Examiner, Art Unit 3663