DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Introduction
Claims 21-41 are pending and have been examined in this Office Action. Claims 1-29 are cancelled. This is the First Office Action on the Merits.
Examiner’s Note
Examiner has cited particular paragraphs / columns and line numbers or figures in the references as applied to the claims below for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested from the applicant, in preparing the responses, to fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner. Applicant is reminded that the Examiner is entitled to give the broadest reasonable interpretation to the language of the claims. Furthermore, the Examiner is not limited to Applicants' definition which is not specifically set forth in the disclosure.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 21-41 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claims 21 is taken as the representative claim. Claim 21 recites obtaining input data, generating a planned action, obtaining a test state, generating a first test response, generating a first exemplar response, generating a second test response, generating a second exemplar response, and evaluating based on comparing the first test response to the first exemplar response and the second test response to the second exemplar response. Therefore, the claim is directed to obtaining data, generating data, and evaluating data, which can be performed in the human mind or with pen and paper. Therefore, the claim is directed to a mental process. Per the specification, see at least paragraph(s) 7 and 11, the exemplar responses can be recorded data. Therefore, even as an ordered combination, the claim amounts to no more than generating test responses and comparing them to recorded data, which is still an abstract idea. This judicial exception is not integrated into a practical application and does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional element of the operational system is merely a generic computer component recited at a high level upon which the part of the abstract idea is intended to be implemented on. That is, aside from “using the operational system, nothing in the claim prevents the claim from being performed within the human mind.
Claim(s) 22-30 is/are rejected because it/they depend(s) from claim 21 and fail(s) to cure the deficiencies above. The dependent claims merely add mental process steps (e.g., obtaining additional data, generating decisions, computing a score) to the abstract idea and do not include any additional elements.
Similar to claims 21-30, claims 31-40 and 41 are directed to the same abstract idea. These claims do not add additional elements that integrated the abstract idea into a mental process or add significantly more because they only add generic computer components recited at a high level upon which the abstract idea is intended to be implemented on. The “vehicle control system”, “processor” and “computer-readable media” merely store the method and do not add a practical application or significantly more.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 21-41 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by U.S. Patent Application Publication 2022/0176993 to De Sapio et al.
As per claim 21, De Sapio discloses a computer-implemented method for hierarchical simulations for evaluating an operational system for controlling an autonomous vehicle (Jiang; At least the abstract), the method comprising:
obtaining input data descriptive of a recorded environment over a time interval (De Sapio; At least paragraph(s) 34);
generating, using the operational system and based on the input data, a planned action to control a subject vehicle in the recorded environment (De Sapio; At least paragraph(s) 34);
obtaining a test state of the subject vehicle in the recorded environment based on the planned action (De Sapio; At least paragraph(s) 34);
generating, starting from the test state, a first test response of the subject vehicle to a first actor action (De Sapio; At least paragraph(s) 36 and 54);
generating, starting from an exemplar state obtained from a recorded exemplar vehicle in the environment, a first exemplar response of the subject vehicle to the first actor action (De Sapio; At least paragraph(s) 62 and 64);
generating, starting from the test state, a second test response of the subject vehicle to a second actor action (De Sapio; At least paragraph(s) 68; the training set can include multiple actors and thus, multiple responses to the different actors);
generating, starting from the exemplar state, a second exemplar response of the subject vehicle to the second actor action (De Sapio; At least paragraph(s) 68); and
evaluating the operational system based on comparing the first test response and the first exemplar response and based on comparing the second test response and the second exemplar response (De Sapio; At least paragraph(s) 65).
As per claim 22, De Sapio discloses generating the planned action over a first portion of the time interval (De Sapio; At least paragraph(s) 47 and 48);
generating a second planned action over a second portion of the time interval (De Sapio; At least paragraph(s) 47 and 54; as new data is obtained, i.e., each time interval; everything is repeated);
obtaining a second test state of the subject vehicle in the recorded environment based on the second planned action (De Sapio; At least paragraph(s) 47);
generating, starting from the second test state, a third test response of the subject vehicle to a third actor action (De Sapio; At least paragraph(s) 36 and 54);
generating, starting from a second exemplar state obtained from the recorded exemplar vehicle in the environment, a third exemplar response of the subject vehicle to the third actor action (De Sapio; At least paragraph(s) 62 and 64);
generating, starting from the second test state, a fourth test response of the subject vehicle to a fourth actor action (De Sapio; At least paragraph(s) 68);
generating, starting from the second exemplar state, a fourth exemplar response of the subject vehicle to the fourth actor action (De Sapio; At least paragraph(s) 68); and
evaluating the operational system based on comparing the third test response and the third exemplar response and based on comparing the fourth test response and the fourth exemplar response (De Sapio; At least paragraph(s) 65).
As per claim 23, De Sapio discloses obtaining the test state of the subject vehicle in the recorded environment based on simulating the subject vehicle executing the planned action in the recorded environment (De Sapio; At least paragraph(s) 63).
As per claim 24, De Sapio discloses inputting simulated sensor data into a simulated autonomous vehicle control system (De Sapio; At least paragraph(s) 34 and 62);
generating, by simulated autonomous vehicle control system, simulated control decisions based on the simulated sensor data (De Sapio; At least paragraph(s) 33); and
obtaining the test state of the subject vehicle based on the simulated control decisions (De Sapio; At least paragraph(s) 34 and 47).
As per claim 25, De Sapio discloses comparing the first test response and the first exemplar response based on a test score computed for the first test response and an exemplar score computed for the first exemplar response (De Sapio; At least paragraph(s) 65).
As per claim 26, De Sapio discloses the test score is based on a test value describing a feature of a motion of the subject vehicle, the feature selected from at least one of a speed, acceleration, jerk, or stopping distance (De Sapio; At least paragraph(s) 69 and 70); and
the exemplar score is based on an exemplar value describing the feature of a motion of the exemplar vehicle (De Sapio; At least paragraph(s) 65).
As per claim 27, De Sapio discloses computing the test value by modeling a projectile trajectory of the motion of the subject vehicle (De Sapio; At least paragraph(s) 65); and
computing the exemplar value by modeling a projectile trajectory of the motion of the exemplar vehicle (De Sapio; At least paragraph(s) 65).
As per claim 28, De Sapio discloses the test score is based on a test margin between a boundary of the subject vehicle and a boundary of an object in the environment (De Sapio; At least paragraph(s) 71); and
the exemplar score is based on an exemplar margin between a boundary of the exemplar vehicle and a boundary of an object in the environment (De Sapio; At least paragraph(s) 65 and 71; to compare the grades, the exemplar would be evaluated in the same way).
As per claim 29, De Sapio discloses the test score is based on a test value for an energy measure associated with a motion of the subject vehicle (De Sapio; At least paragraph(s) 74); and
the exemplar score is based on an exemplar value for the energy measure associated with a motion of the exemplar vehicle (De Sapio; At least paragraph(s) 74).
As per claim 30, De Sapio discloses deploying, based on the evaluation of the operational system, the operational system to an autonomous vehicle control system (De Sapio; At least paragraph(s) 65).
As per claims 31-38 and 41, De Sapio discloses an autonomous vehicle control system and computing system (De Sapio; At least paragraph(s) 27 and 30) based on or to perform the method of claims 21-26, 28, and 29. Therefore, claims 31-38 and 41 are rejected using the same citations and reasoning as applied to claims 21-26, 27, and 28.
As per claim 39, De Sapio discloses comprising:
one or more processors (De Sapio; At least paragraph(s) 30); and
one or more non-transitory computer-readable media storing instructions that are executable by the one or more processors to cause the autonomous vehicle control system to perform operations (De Sapio; At least paragraph(s) 30), the operations comprising:
obtaining sensor data descriptive of an environment (De Sapio; At least paragraph(s) 34);
generating, using the operational system and based on the sensor data, an action for the autonomous vehicle in the environment (De Sapio; At least paragraph(s) 34); and
executing the action to control an operation of the autonomous vehicle in the environment (De Sapio; At least paragraph(s) 25 and 27).
As per claim 40, De Sapio discloses executing the action to control a motion of the autonomous vehicle in the environment, wherein the operational system comprises a motion planning system, and wherein the action corresponds to a motion plan generated by the motion planning system (De Sapio; At least paragraph(s) 25, 26, and 34).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. See PTO-892. The prior art shows the state of the art.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DAVID P MERLINO whose telephone number is (571)272-8362. The examiner can normally be reached M-Th 5:30am-3:00pm F 5:30-9:00 am ET.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Erin Bishop can be reached at 571-270-3713. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/David P. Merlino/Primary Examiner, Art Unit 3665