Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
The amendment filed December 24, 2025 has been entered. Claims 1-20 remain
pending in the application.
Response to Arguments
Applicant's arguments filed December 24, 2025 have been fully considered but are not persuasive. Applicant argued that the Wendel does not anticipated the amended independent claims.
In this office action, the amended independent claims are rejected under 35 USC 103 over Wendel in view of Singh.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1, 2, 3, 5, 7-11, 13, 15-17 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Wendel et al. (US 20190258263 A1) in view of Singh et al. (US 20250222945 A1).
Regarding claim 1, Wendel discloses: a method, comprising: obtaining a plurality of images captured by a plurality of cameras of a vehicle {[0017]: cameras mounted within the vehicle}; generating, using artificial intelligence (AI) and the plurality of images, a plurality of passenger data indicating locations of one or more passengers of the vehicle {[0018] discloses AI model: using the cameras, a model may be generated... machine learning techniques. [0057] discloses passenger location: where the passengers are sitting}.
Wendel does not disclose: using AI includes using a plurality of artificial intelligence (AI) model, wherein each of the plurality of passenger data is provided by one of the plurality of AI models with at least one respective confidence score.
Singh teaches using a plurality of AI models in paragraph [0232]: machine learning models are used; [0241]: sensor data may be processed using one or more machine learning models… the output may be compared}; [0297]: an artificial intelligence module comprising machine learning models; passenger data in [0150]: sensor data is used to detect an occupant of the vehicle; [0174]: images of occupants; confidence in [0229]: the machine learning model, based on the features of the received data and occupant profiles, may generate a score representing a likelihood or confidence.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the AI models and confidence features of Singh with the described invention of Wendel in order to improve passenger detection by trying more than one AI models.
Wendel further discloses: generating, based on the plurality of passenger data and the respective confidence scores, vehicle area data indicating one or more areas of the vehicle at which the one or more passengers are located {[0017] discloses vehicle are data: locations where passengers are likely to be seated, or underneath the seats and into the cargo areas}; determining, based on the passenger data and the vehicle area data, whether at least one passenger seating configuration criterion is satisfied {[0082] discloses passenger seating configuration criterion: passengers have unbuckled a seatbelt, and/or have gotten out of a seat}; and responsive to determining that the at least one passenger seating configuration criterion is satisfied, causing the vehicle to perform an action associated with a passenger seating configuration in the vehicle {[0082], [0022] discloses performing an action associated with a passenger seating configuration: a responsive action or how the vehicle is to respond to a determined internal state of the vehicle}.
Similar reasoning applies to claims 9, 17.
Regarding claim 2, which depends from claim 1, Wendel discloses: wherein: the vehicle comprises an autonomous vehicle (AV) {[0015]: autonomous vehicle}; and the action associated with the passenger seating configuration in the vehicle comprises at least one of: producing a passenger alert based on the at least one passenger seating configuration criterion being satisfied, or autonomously modifying operation of the AV based on the at least one passenger seating configuration criterion being satisfied {[0003] discloses passenger alert and modifying operation of the AV based on the passenger seating configuration criterion: providing a notification that indicates that the child must be in a specific seat within the vehicle… the responsive action includes not starting a trip until the child is the appropriate child restraint}.
Similar reasoning applies to claims 10, 20.
Regarding claim 3, which depends from claim 2, Wendel discloses: wherein autonomously modifying the operation of the AV comprises causing a control system of the AV to perform at least one of: preventing the AV from driving; or causing the AV to stop {[0003]}.
Similar reasoning applies to claim 11.
Regarding claim 5, which depends from claim 1, Wendel discloses: wherein the one or more areas of the vehicle comprise: one or more seats of the vehicle; a floor of the vehicle; and a storage area of the vehicle {[0017]: view locations where passengers are likely to be seated, or underneath the seats and into the cargo areas}.
Similar reasoning applies to claim 13.
Regarding claim 7, which depends from claim 1, Wendel discloses: wherein the at least one passenger seating configuration criterion comprises at least one of: a first passenger of the one or more passengers being located in a first seat of the vehicle, and seatbelt data of the vehicle indicating that a seatbelt of the first seat is not buckled; a plurality of passengers of the one or more passengers being located in the first seat of the vehicle; or the first passenger being located in a first area of the one or more areas of the vehicle, and the first area not being a seat of the vehicle {[0082]: whether passengers have unbuckled a seatbelt, and/or have gotten out of a seat}.
Similar reasoning applies to claim 15.
Regarding claim 8, which depends from claim 1, Wendel discloses: wherein the at least one passenger seating configuration criterion comprises at least one of: each passenger located in each seat of the vehicle being identified as a child passenger; a first passenger of the one or more passengers being identified as a child passenger, and the first passenger not being seated in a child safety seat; or a second passenger of the one or more passengers smoking {[0003]: when the determined internal state indicates that a child is in the vehicle… the child must be in a specific seat within the vehicle... not starting a trip until the child is the specific seat of the vehicle. [0057]: whether a passenger is an adult or child}.
Similar reasoning applies to claim 16.
Claim(s) 4, 12, 18 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Wendel in view of Singh and in further view of Pertsel et al. (US 10953850 B1), which was cited by Applicant.
Regarding claim 4, which depends from claim 1, modified Wendel does not teach: wherein using the plurality of AI models and the plurality of images comprises at least one of: generating a panoramic image from the plurality of images and using the panoramic image as input to the plurality of AI models; or generating an embedding based on the plurality of images and using the embedding as input to the plurality of AI models.
Pertsel teaches generating a panoramic image in col. 4, lines 3-5: The panoramic video may comprise a large field of view generated by one or more lenses/camera sensors.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the panoramic image feature of Pertsel with the described invention of modified Wendel in order to facilitate figuring out the entire interior of a vehicle.
Regarding claim 12, which depends from claim 9, Pertsel teaches: wherein using the plurality of AI models and the plurality of images comprises at least one of: generating a panoramic image from the plurality of images; or generating an embedding based on the plurality of images {col. 4, lines 3-5}.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the panoramic image feature of Pertsel with the described invention of modified Wendel in order to facilitate figuring out the entire interior of a vehicle.
Regarding claim 18, which depends from claim 17, Pertsel teaches: wherein the passenger data comprises, for each location of the one or more locations of the one or more passengers, a respective confidence score {col. 16, lines 35-36: to determine a confidence level of the status of the seat belt}.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the confidence score feature of Pertsel with the described invention of modified Wendel in order to improve reliability of passenger data.
Regarding claim 19, which depends from claim 18, modified Wendel teaches: wherein: the passenger data comprises first passenger data generated by a first AI model of the plurality of AI models, wherein the first passenger data indicates that a first location of the one or more location of the vehicle includes a passenger of the one or more passengers; the passenger data further comprises second passenger data generated by a second AI model of the plurality of AI models, wherein the second passenger data indicates that the first location does not include a passenger of the one or more passengers; the operations further comprise determining that a respective confidence score of the first passenger data is higher than a respective confidence score of the second passenger data; and generating the vehicle area data is based on the first passenger data {Wendel: [0057], / Singh: [0232], [0241], [0297], [0150], [0174], [0229]}.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the AI models and confidence features of Singh with the described invention of modified Wendel in order to improve passenger detection by trying more than one AI models.
Claim(s) 6 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Wendel in view of Singh and in further view of Kim et al. (KR102643149B1).
Regarding claim 6, which depends from claim 1, modified Wendel does not teach: wherein generating the vehicle area data based on the passenger data comprises: determining a location of a passenger of the one or more passengers; and determining whether the location of the passenger overlaps above a threshold amount with a location of an area of the one or more areas of the vehicle.
Kim teaches to determine overlap of passenger location with an are location in claim 9: The passenger detection result… to determine the position of the non-seat passenger. A first area is divided into an area where the first input image and the second input image overlap each other. Use of a threshold amount is implied in the determination process.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the passenger data overlap feature of Kim with the described invention of modified Wendel in order to facilitate determining the position of a non-seat passenger.
Similar reasoning applies to claim 14.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Shetty et al. (US 20250065844 A1) teaches using AI models for analyzing passenger data.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/C.P./Examiner, Art Unit 3661
/RUSSELL FREJD/Primary Examiner, Art Unit 3661