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 Claims
This Office Action is in response to the Office Action Response dated October 22, 2025. Claims 1-6 and 8-10 are presently pending and are presented for examination.
Response to Arguments
With respect to the rejections under 35 USC 101, Applicant have not presented arguments why the presented amendments overcome this rejection. Additionally, the newly added features to the independent claim merely indicates the source of data being analyzed and what information is being stored based upon the analysis.
With respect to the rejections under 35 USC 103, Applicant arguments are moot in view of new grounds of rejection.
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 1-6, 9 and 10 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an Abstract idea without significantly more.
Regarding Prong I of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the follow groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes.
With respect to claim 1, and similarly with respect to claims 9 and 10, the claims recites:
Claims 1/9/10: A method of generating a digital model-based representation of a vehicle, comprising the following steps / A computing unit configured to generate a digital model-based representation of a vehicle, the computing unit configured to / A computer-readable storage medium on which is stored a computer program for generating a digital model-based representation of a vehicle, the computer program, when executed by a data processor, causing the data processor to perform the following steps:
A) receiving sensor data of a plurality of acoustic sensors of the vehicle, wherein the sensor data describe sounds of the vehicle and/or sounds of an environment of the vehicle, and wherein the sensor data are recorded for a plurality of trips of the vehicle;
B) evaluating the sensor data and determining relations between: (i) the recorded sounds of the vehicle and/or of the environment, and (ii) respective states of the vehicle and/or of the environment causing the respective sounds; and
C) storing, in a model-based representation of the vehicle, the determined relations between the sounds of the vehicle and/or of the environment and the respective states of the vehicle and/or of the environment, wherein the stored relations are based on sensor data recorded from the vehicle during the plurality of trips; wherein the model-based representation of the vehicle is formed as a digital twin of the vehicle wherein the digital twin captures relations between vehicle component sounds and corresponding vehicle states as well as environment sounds and corresponding environment states.
The examiner submits that the foregoing bolded limitation(s) constitute “mental processes” because under its broadest reasonable interpretation, the claims cover performing an evaluation of data to determine a state of a vehicle or environment, which may be performed in the human mind or by hand.
Regarding Prong II of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract into a practical application. As noted in the 2019 PEG, it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined portions are the “additional limitations” while the bolded portions continue to represent the “abstract idea”)
Claims 1/9/10: A method of generating a digital model-based representation of a vehicle, comprising the following steps / A computing unit configured to generate a digital model-based representation of a vehicle, the computing unit configured to / A computer-readable storage medium on which is stored a computer program for generating a digital model-based representation of a vehicle, the computer program, when executed by a data processor, causing the data processor to perform the following steps:
A) receiving sensor data of a plurality of acoustic sensors of the vehicle, wherein the sensor data describe sounds of the vehicle and/or sounds of an environment of the vehicle, and wherein the sensor data are recorded for a plurality of trips of the vehicle;
B) evaluating the sensor data and determining relations between: (i) the recorded sounds of the vehicle and/or of the environment, and (ii) respective states of the vehicle and/or of the environment causing the respective sounds; and
C) storing, in a model-based representation of the vehicle, the determined relations between the sounds of the vehicle and/or of the environment and the respective states of the vehicle and/or of the environment, wherein the stored relations are based on sensor data recorded from the vehicle during the plurality of trips; wherein the model-based representation of the vehicle is formed as a digital twin of the vehicle wherein the digital twin captures relations between vehicle component sounds and corresponding vehicle states as well as environment sounds and corresponding environment states.
For the following reason(s), the examiner submits that the above identified additional limitations do not integrate the above-noted abstract idea into a practical application.
Regarding the additional limitations of “receiving sensor data,” the examiner submits that merely receiving data is an extra solution activity that is well-understood, routine and/or conventional activities in the field of the particular claim. See MPEP 2106.05(d).
Regarding the additional limitations of “storing…the determined relations,” the examiner submits that storing the end results of an evaluation is also well-understood, routine and/or conventional activities in the field of the particular claim. See MPEP 2106.05(d).
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitation(s) as an ordered combination or as a whole, the limitation(s) add nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is not more than a drafting effort designed to monopolize the exception (MPEP § 2106.05). Accordingly, the additional limitation(s) do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Regarding Step 2B of the Revised Guidance, representative independent claims 1/9/10 do not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application. Additionally, as discussed above with respect to integration of the abstract idea into a practical application, the additional element of receiving data to be analyzed and storing the results of the analysis does not utilized the process data in a meaningful way to change the operation of the system or control the system. Hence, the claims are not patent eligible.
Dependent claims 2-6 do not recite any further limitations that cause the claim(s) to be patent eligible. Rather, the limitations of dependent claims are directed toward judicial exceptions, additional aspects of the judicial exception and/or well-understood, routine and conventional additional elements that do not integrate the judicial exception into a practical application.
Claim Rejections - 35 USC § 103
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 1-6 and 8-10 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Publication No. 2021/0166719, to Young et al. (hereinafter Young), in view of U.S. Patent Publication No. 2023/0184560, to Che et al. (hereinafter Che), and in further view of U.S. Patent Publication No. 2015/0120336, to Grokop et al. (hereinafter Grokop).
As per claim 1, and similarly with respect to claims 9 and 10, Young discloses a method of generating a digital model-based representation of a vehicle (e.g. see Abstract, wherein a method of determining vehicle location based upon the mapping of audio data of an environment is provided), comprising the following steps: receiving sensor data of a plurality of acoustic sensors of the vehicle (e.g. see Abstract, Fig. 1, and para 0030, wherein a system 20 is provided including sensors 21, such as first and second audio sensors), wherein the sensor data describe sounds of the vehicle and/or sounds of an environment of the vehicle (e.g. see para 0006, wherein an environmental condition proximate to the sensors are identified), and wherein the sensor data are recorded for a plurality of trips of the vehicle (e.g. see para 0048, audio sensor data is compared to past recorded audio sensor data; and see para 0025, wherein HD maps are generated and updated based upon the sensor data from a host vehicle meaning that the sensor capturing feature is continually repeated); evaluating the sensor data and determining relations between: (i) the recorded sounds of the vehicle and/or of the environment, and (ii) respective states of the vehicle and/or of the environment causing the respective sounds (e.g. see para 0004, wherein an extracted feature of the audio is used to estimate a road features (i.e. environmental feature causing the respective sounds)); and storing, in a model-based representation of the vehicle, the determined relations between the sounds of the vehicle and/or of the environment and the respective states of the vehicle and/or of the environment (e.g. see para 0025, wherein maps (i.e. model-based representation of the vehicle) are updated (i.e. stored) based upon the recorded audio for navigation of an autonomous vehicle with respect to an identified feature (i.e. relationship between environmental sound and state of the environment)), wherein the stored relations are based on sensor data recorded from the vehicle during the plurality of trips (e.g. see para 0048, audio sensor data is compared to past recorded audio sensor data; and see para 0025, wherein HD maps are generated and updated based upon the sensor data from a host vehicle meaning that the sensor capturing feature is continually repeated (i.e. the updated maps stored the relationship based upon captured data during a plurality of trips)).
Young fails to disclose wherein the model-based representation of the vehicle is formed as a digital twin wherein the digital twin captures relations between…environment sounds and corresponding environment states. However, Che teaches a vehicle display system that depicts a model of a host vehicle (i.e. digital twin) on a map based upon real-time position of the host vehicle determined by a positioning system (i.e. sensors) (e.g. see Fig. 3, paras 0010 and 0051). It is further noted that Young discloses positioning of the vehicle may be determined through acoustic positioning sensors. It would have been obvious to a person of ordinary skill in the art at the time of Applicants’ invention to modify the vehicle display system of Young to include displaying a visual twin of a host vehicle, for the purpose of providing a more visual pleasing experience for the driver, as well as improve differentiation of the host vehicle from surrounding vehicles.
Young and Che fail to disclose wherein the model-based representation of the vehicle is formed as a digital twin wherein the digital twin captures relations between vehicle components sounds and corresponding vehicle states… However, Grokop teaches identifying a model of a vehicle (i.e. forming a digital twin) based upon captured sounds of the vehicle (e.g. turn signal and engine sounds) corresponding to a state of the vehicle (e.g. turning, accelerating, etc.) (e.g. see para 0349). It would have been obvious to a person of ordinary skill in the art at the time of Applicants’ invention to modify the vehicle display system of Young to include displaying a visual twin of a host vehicle, for the purpose of providing a more visual pleasing experience for the driver, as well as improve differentiation of the host vehicle from surrounding vehicles through vehicle identification.
As per claim 2, Young, as modified by Che and Grokop, teaches the features of claim 1, and further discloses wherein the sounds of the vehicle include: sounds of a motor and/or a transmission and/or a chassis and/or a shock absorption and/or a wheel suspension and/or of brakes, and/or of tires and/or a body of the vehicle, and wherein the respective states of the vehicle include: functional states of the motor and/or the transmission and/or the chassis and/or the shock absorption and/or the wheel suspension and/or the tires and/or the body and/or a speed and/or a loading state of the vehicle and/or a rolling resistance of the tires on a travel lane and a state of the travel lane and/or a coating of the body with moisture or snow or dust or dust or leaves (e.g. the Office notes that since claim 1 is in an alternative form (i.e. sounds/states of vehicle or environment, and the prior art reference is related to environment sound/state, this claim fails to further limit the subject matter of claim 1, with respect to the prior art being applied).
As per claim 3, Young, as modified by Che and Grokop, teaches the features of claim 1, and further discloses wherein the sounds of the environment include: sounds of further vehicles and/or sounds of pedestrians and/or sounds of animals and/or sounds of the vehicle reflected by buildings or vegetation situated in the environment and/or sounds of precipitation and/or sounds of snowfall and/or sounds of hail and/or sounds of wind, and wherein states of the environment of the vehicle include: a presence of vehicles and/or a presence of pedestrians and/or a presence of buildings and/or a presence of vegetation and/or a presence of precipitation and/or a presence of hail and/or a presence of snow (e.g. see para 0067, wherein one of the sounds picked up by the sensors includes rain which is used to change the baseline of road events).
As per claim 4, Young, as modified by Che and Grokop, teaches the features of claim 3, and further discloses further comprising detection of the objects in the environment including a position determination of the objects in the environment and/or a determination of a distance of the objects and/or a determination of a speed of the objects relative to the vehicle and/or a characterization of the objects (e.g. see Fig. 6, and para 0026, wherein the sound used to detect environmental objects including a road surface includes a characterization of the road, such as potholes, cracks, bumps, etc.).
As per claim 5, Young, as modified by Che and Grokop, teaches the features of claim 1, and further discloses wherein the sensor data include acoustic data of a plurality of microphones and/or data of a plurality of ultrasonic sensors (e.g. see para 0030, wherein the sensors comprise microphones).
As per claim 6, Young, as modified by Che and Grokop, teaches the features of claim 1, and further discloses wherein the determining of the relations between the sounds of the vehicle and/or of the environment and the respective states of the vehicle and/or of the environment includes performing machine learning techniques on the sensor data, and wherein the storing of the determined relations includes storing a correspondingly trained artificial intelligence or a plurality of correspondingly trained artificial intelligences (e.g. see para 0040, wherein the maps are formed through machine learning technique utilizing a database of recorded data).
As per claim 8, Young discloses a method of controlling a vehicle (e.g. see para 0023, wherein maps are generated based upon audio events which are used for controlling travel of autonomous vehicles), comprising the following steps: receiving acoustic sensor data of a plurality of acoustic sensors of the vehicle, wherein the acoustic sensor data describe sounds of the vehicle and/or sound of an environment of the vehicle (e.g. see Abstract, Fig. 1, and para 0030, wherein a system 20 is provided including sensors 21, such as first and second audio sensors; and see para 0006, wherein an environmental condition proximate to the sensors are identified);
executing a model-based representation of the vehicle on the acoustic sensor data, wherein the model-based representation of the vehicle is generated by: receiving sensor data of a plurality of acoustic sensors of the vehicle, wherein the sensor data describe sounds of the vehicle and/or sounds of an environment of the vehicle, and wherein the sensor data are recorded for a plurality of trips of the vehicle, evaluating the sensor data and determining relations between: (i) the recorded sounds of the vehicle and/or of the environment, and (ii) respective states of the vehicle and/or of the environment causing the respective sounds, and storing, in the model-based representation of the vehicle, the determined relations between the sounds of the vehicle and/or of the environment and the respective states of the vehicle and/or of the environment, wherein the stored relations are based on sensor data recorded from the vehicle during the plurality of trips (e.g. see rejection of claim 1);
determining a state of the vehicle and/or a state of the environment of the vehicle based on the acoustic sensor data of the vehicle and the relations stored in the model-based representation of the vehicle; and outputting control signals for controlling the vehicle taking into account the determined state of the vehicle and/or the determined state of the environment of the vehicle (e.g. see para 0023-0026, wherein the position of the vehicle is determined based upon a state of a road surface (e.g. presence of road cracks, bumps, etc., which is used to generate and transmit control signals for the autonomous vehicle; the Office further notes that the state of the road is determined based upon sensor data and previously recorded historical data at the same location of the road).
Young fails to disclose wherein the model-based representation of the vehicle is formed as a digital twin wherein the digital twin captures relations between…environment sounds and corresponding environment states. However, Che teaches a vehicle display system that depicts a model of a host vehicle (i.e. digital twin) on a map based upon real-time position of the host vehicle determined by a positioning system (i.e. sensors) (e.g. see Fig. 3, paras 0010 and 0051). It is further noted that Young discloses positioning of the vehicle may be determined through acoustic positioning sensors. It would have been obvious to a person of ordinary skill in the art at the time of Applicants’ invention to modify the vehicle display system of Young to include displaying a visual twin of a host vehicle, for the purpose of providing a more visual pleasing experience for the driver, as well as improve differentiation of the host vehicle from surrounding vehicles.
Young and Che fail to disclose wherein the model-based representation of the vehicle is formed as a digital twin wherein the digital twin captures relations between vehicle components sounds and corresponding vehicle states… However, Grokop teaches identifying a model of a vehicle (i.e. forming a digital twin) based upon captured sounds of the vehicle (e.g. turn signal and engine sounds) corresponding to a state of the vehicle (e.g. turning, accelerating, etc.) (e.g. see para 0349). It would have been obvious to a person of ordinary skill in the art at the time of Applicants’ invention to modify the vehicle display system of Young to include displaying a visual twin of a host vehicle, for the purpose of providing a more visual pleasing experience for the driver, as well as improve differentiation of the host vehicle from surrounding vehicles through vehicle identification.
Conclusion
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to James M. McPherson whose telephone number is (313) 446-6543. The examiner can normally be reached on 7:30 AM - 5PM Mon-Fri Eastern Alt Fri. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Abby Flynn can be reached on 571 272-9855. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JAMES M MCPHERSON/Primary Examiner, Art Unit 3663B
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