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 .
Status of the Claims
This action is in response to the applicant’s filing on August 28, 2024. Claims 1-19 are pending and are examined below.
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 1-7, and 10-17 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Claims 1-7, and 10-17 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claims 1-7, and 10-17 are directed to the abstract idea of optimizing a route for a vehicle, which is an abstract idea under its broadest reasonable interpretation because the claimed invention is directed to an observation, evaluation and/or judgment as to how to optimize a route for a vehicle based on various criteria, notably, availability of autonomous driving and remote driving along route segments. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements are either directed to insignificant extra-solution activity, i.e., displaying results, or generically training a model, to provide conventional functions that do not add meaningful limits to practicing the abstract idea.
Claim 1 recites a method for route building, comprising: determining an autonomous driving availability for a route based on at least one performance metric for a plurality of locations along the route, wherein the autonomous driving availability is availability of a vehicle to operate based on instructions from at least one system of the vehicle; determining a remote driving availability for the route based on expected network conditions at the plurality of locations along the route, wherein the remote driving availability is availability of the vehicle to operate based on instructions from a remote system which is remote from the vehicle; and optimizing the route by applying a weighted graph algorithm to a plurality of values representing at least the autonomous driving availability and the remote driving availability along the route, wherein the route is optimized such that at least a first portion of the route is navigated using autonomous driving and at least a second portion of the route is navigated using remote driving.
Under it its broadest reasonable interpretation, the claim recites a mental process because optimizing a route for a vehicle is an example of an observation, evaluation and/or judgment, and observations, evaluations and/or judgments are examples of abstract ideas.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claim does not include any additional elements beyond mental steps.
Independent claims 10 and 11 are rejected under the same rationale as claim 1 because the claims recited nearly identical subject matter but for minor differences, specifically, the inclusion of additional insignificant elements, i.e., processing circuitry, and memory, that do no render an invention eligible.
Claims 2-7, and 12-17 depend on claims 1, and 11 but do not render the claimed invention eligible because they are directed to insignificant additional elements including insignificant pre-solution activity, i.e., receiving an input, etc., additional mental steps directed to the above described mental process, i.e., determining an amount of remote driving service available to a user during a given time period, etc., or generically training a machine learning model to implement the abstract idea.
Claims 8, 9, 18, and 19 recite positive vehicle control that would render the claimed invention eligible subject matter if independent claim 1 was amended to incorporate those limitations.
Independent claims 10 and 11 are rejected under the same rationale as claim 1 because the claims recited nearly identical subject matter but for minor differences, specifically, the inclusion of additional insignificant elements, i.e., processing circuitry, and memory, that do no render an invention eligible.
Claims 1-14 are therefore not drawn to eligible subject matter as they are directed to an abstract idea without significantly more.
Claim Rejections - 35 USC § 102
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 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.
Claims 1-3, 5, 6, 9-13, 15, 16, and 19 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Srinivasan et al., US 20200239023 A1, hereinafter referred to as Srinivasan.
As to claim 1, Srinivasan discloses a method for route building, comprising:
determining an autonomous driving availability for a route based on at least one performance metric for a plurality of locations along the route, wherein the autonomous driving availability is availability of a vehicle to operate based on instructions from at least one system of the vehicle (Routing according to autonomous vehicle metrics – See at least ¶23);
determining a remote driving availability for the route based on expected network conditions at the plurality of locations along the route, wherein the remote driving availability is availability of the vehicle to operate based on instructions from a remote system which is remote from the vehicle (Routing according to remote operator assistance – See at least ¶27); and
optimizing the route by applying a weighted graph algorithm to a plurality of values representing at least the autonomous driving availability and the remote driving availability along the route, wherein the route is optimized such that at least a first portion of the route is navigated using autonomous driving and at least a second portion of the route is navigated using remote driving (Lowest cost, i.e., optimization – See at least ¶22; Cost indicative of traversal between route components – See at least ¶22; Routing graph and constraint data used to generate route – See at least ¶80; Costs may be changed up or down based on costs to traverse favored/disfavored route segments – See at least ¶84; Routing cost may indicative of requirement of remote operation versus autonomous control – See at least ¶93).
Independent claims 10 and 11 are rejected under the same rationale as claim 1 because the claims recite nearly identical subject matter but for minor differences due to the claims being directed to different stator categories of invention.
As to claims 2, and 12, Srinivasan discloses determining an amount of remote driving service available to a user of the vehicle during a time period in which the route is to be navigated, wherein the route is optimized based further on the amount of remote driving service (Lowest cost, i.e., optimization – See at least ¶22; Cost indicative of traversal between route components – See at least ¶22; Routing cost may indicative of requirement of remote operation versus autonomous control – See at least ¶93; Examiner notes a plurality of route segments where remote driving occurs is analogous to the claimed “amount.”).
As to claims 3, and 13, Srinivasan discloses identifying at least one service provider location with respect to the route based on a service request, wherein the route is optimized based further on the at least one service provider location (Route segment/component locations – See at least ¶36; Remote assistance locations – See at least ¶40).
As to claims 5, and 15, Srinivasan discloses determining the autonomous driving availability by inputting at least one first location of the plurality of locations along the route to a machine learning model, wherein the machine learning model is trained to estimate autonomous driving availability at a location of each of the at least one first location, wherein the machine learning model is trained based on a training data set including at least one driving performance metric measured at the location of each of the at least one first location (Prediction system including machine-learned models – See at least ¶67).
As to claims 6, and 16, Srinivasan discloses determining the remote driving availability by inputting at least one first location of the plurality of locations along the route to a machine learning model, wherein the machine learning model is trained to estimate remote driving availability at a location of each of the location, wherein the machine learning model is trained based on a training data set including historical network condition data for the location of each of the at least one first location (Prediction system including machine-learned models – See at least ¶67).
As to claims 9, and 19, Srinivasan discloses executing the optimized route by causing the vehicle to navigate using autonomous driving during at least the first portion of the route and to navigate using remote driving during at least the second portion of the route (Execute selected route – See at least ¶111 and Fig. 7).
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.
Claims 4, and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Srinivasan et al., US 20200239023 A1, in view of Allen et al., US 20250074454 A1, hereinafter referred to as Srinivasan, and Allen, respectively.
As to claims 4, and 14, Srinivasan fails to explicitly disclose training a machine learning model to learn user preferences of a user with respect to remote driving, wherein the machine learning model is trained using a training data set including previous usage of remote driving capabilities by the user, wherein the route is optimized based further on the learned user preferences. However, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Srinivasan and include the feature of training a machine learning model to learn user preferences of a user with respect to remote driving, wherein the machine learning model is trained using a training data set including previous usage of remote driving capabilities by the user, wherein the route is optimized based further on the learned user preferences, with a reasonable expectation of success, because Allen teaches it is well-known and routine in the autonomous vehicle arts to train a model that reflects user preferences (See at least Abstract of Allen).
Claims 7, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Srinivasan et al., US 20200239023 A1, in view of Anabuki et al., US 20220234625 A1, hereinafter referred to as Srinivasan, and Anabuki, respectively.
As to claims 7, and 17, Srinivasan discloses the optimized route is a first optimized route for a first route among a plurality of routes, further comprising: determining an autonomous driving availability and a remote driving availability for each of the plurality of routes; and optimizing each of the plurality of routes in order to create a plurality of optimized routes including the first optimized route (System generates routes – See at least ¶21 and ¶60; Examiner notes Srinivasan’s use of plural routes is indicative of a plurality of routes similar to the claim language.).
Srinivasan fails to explicitly disclose presenting each of the plurality of optimized routes to a user. However, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Srinivasan and include the feature of presenting each of the plurality of optimized routes to a user, with a reasonable expectation of success, because Anabuki teaches it is well-known and routine in the vehicle navigation arts to present a user with a plurality of routes (See at least ¶54 of Anabuki).
Claims 8, and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Srinivasan et al., US 20200239023 A1, in view of Slusar, US 11466999 B1, hereinafter referred to as Srinivasan, and Slusar, respectively.
As to claims 8, and 18, Srinivasan fails to explicitly disclose: receiving a selection of one of the plurality of optimized routes from the user; and executing the selected route. However, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Srinivasan and include the feature of receiving a selection of one of the plurality of optimized routes from the user and executing the selected route, with a reasonable expectation of success, because Slusar teaches it is well-known and routine in the autonomous vehicle control arts to control a vehicle according to a user-selected route (See at least Claim 1 of Slusar).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Lail Kleinman whose telephone number is (571)272-6286. The examiner can normally be reached M-F 8:00-5:00.
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/LAIL A KLEINMAN/Primary Examiner, Art Unit 3668