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 .
Claim Objections
Claims 5, 6, 9, 16, 17, and 20 are objected to because of the following informalities.
• Claim 5, line 2, “a maneuver” should read as “the maneuver”.
• Claim 6, line 2, “a steering command” should read as “the steering command”.
• Claim 9, lines 1-2, “a steering command” should read as “the steering command”.
• Claim 9, line 2, “a braking command” should read as “the braking command”.
• Claim 9, line 2, “an acceleration command” should read as “the acceleration command”.
• Claim 9, lines 2-3, “a voice command” should read as “the voice command”.
• Claim 9, line 3, “a maneuver” should read as “the maneuver”.
• Claim 16, line 2, “a maneuver” should read as “the maneuver”.
• Claim 16, line 2, “a steering command” should read as “the steering command”.
• Claim 17, line 2, “a steering command” should read as “the steering command”.
• Claim 20, lines 1-2, “a steering command” should read as “the steering command”.
• Claim 20, line 2, “a braking command” should read as “the braking command”.
• Claim 20, line 2, “an acceleration command” should read as “the acceleration command”.
• Claim 20, line 2, “a voice command” should read as “the voice command”.
• Claim 20, line 3, “a maneuver” should read as “the maneuver”.
Appropriate correction is required.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: Does the claimed invention fall inside one of the four statutory categories (process, machine, manufacture, or composition of matter)? Yes for claims 1-20.
Claims 1-9 are drawn to an assistance system for training a shared-driving model (i.e., a manufacture). Claims 10-11 are drawn to a non-transitory computer-readable medium for training a shared-driving model (i.e., a manufacture). Claims 12-20 are drawn to a method for training a shared-driving model (i.e., a process).
Step 2A - Prong One: Do the claims recite a judicial exception (an abstract idea enumerated in the 2019 PEG, a law of nature, or a natural phenomenon)? Yes, for claims 1-20.
Claim 1 recites:
An assistance system comprising: a memory storing instructions that, when executed by a processor, cause the processor to: acquire a driving suggestion from an assisting operator associated with a driving scenario involving a vehicle;
receive a driving command and vocal data from the vehicle about following the driving suggestion during the driving scenario;
and train a shared-driving model using the driving suggestion, the driving command, and the vocal data.
These steps amount to a form of mental process and organizing human activity (i.e., an abstract idea) because a human can obtain a driving suggestion from an operator and vocally provide driving instructions associated with the driving suggestion. Applicant of claimed invention discloses “the system iteratively updates the parameters using feedback about the training data given by a human observer that rates the predicted values” [0003].
Independent claims 10 and 12 describe nearly identical steps as claim 1 (and therefore recite limitations that fall within this subject matter of grouping abstract ideas), and these claims are therefore determined to recite an abstract idea under the same analysis. Dependent claims 2-9, 11, and 13-20 are directed towards mini-tasks (communicating feedback regarding the driving suggestion, controlling the vehicle based on the driving suggestion, and ignoring driving suggestions, etc.) for an assistance system for training a shared-driving model. Each claim amounts to a form of collecting, generating, and analyzing information, and therefore falls within the scope of a method for organizing human activity, (i.e., an abstract idea). As such, the Examiner concludes that claims 2-9, 11, and 13-20 recite an abstract idea.
Step 2A – Prong Two: Do the claims recite additional elements that integrate the exception into a practical application of the exception? No
In prong two of step 2A, an evaluation is made whether a claim recites any additional element, or combination of additional elements, that integrate the exception into a practical application of that exception. An “additional element” is an element that is recited in the claim in addition to (beyond) the judicial exception (i.e., an element/limitation that sets forth an abstract idea is not an additional element). The phrase “integration into a practical application” is defined as requiring an additional element or a combination of additional elements in the claim to apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that it is more than a drafting effort designed to monopolize the exception.
The requirement to execute the claimed steps/functions using computing devices (independent claims 1, 10, and 12 and dependent claims 2-9, 11 and 13-20) is equivalent to adding the words “apply it” on a generic computer and/or mere instructions to implement the abstract idea on a generic computer. Similarly, the limitations of memory, processors, and computer-readable mediums (independent claims 1, 10, and 12 and dependent claims 2-9, 11 and 13-20) are recited at a high level of generality and amount to no more than mere instructions to apply the exception using generic computer components. These limitations do not impose any meaningful limits on practicing the abstract idea, and therefore do not integrate the abstract idea into a practical application (see MPEP 2106.05(f)).
Use of a computer, processor, memory or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015) (See MPEP 2106.05(f)).
Further, the additional limitations beyond the abstract idea identified above, serve merely to generally link the use of the judicial exception to a particular technological environment or field of use. Specifically, they serve to limit the application of the abstract idea to a computerized environment (e.g., acquiring and receiving, etc.) performed by memory, processors, and computer-readable mediums, etc. This reasoning was demonstrated in Intellectual Ventures I LLC v. Capital One Bank (Fed. Cir. 2015), where the court determined “an abstract idea does not become nonabstract by limiting the invention to a particular field of use or technological environment, such as the Internet [or] a computer”). These limitations do not impose any meaningful limits on practicing the abstract idea, and therefore do not integrate the abstract idea into a practical application (see MPEP 2106.05(h)).
Dependent claims 2-9, 11, and 13-20 fail to include any additional elements. In other words, each of the limitations/elements recited in respective dependent claims are further part of the abstract idea as identified by the Examiner for each respective independent claim (i.e., they are part of the abstract idea recited in each respective claim). The Examiner has therefore determined that the additional elements, or combination of additional elements, do not integrate the abstract idea into a practical application. Accordingly, the claims are directed to an abstract idea.
Step 2B: Does the claim as a whole amount to significantly more than the judicial exception? i.e., Are there any additional elements (features/limitations/step) recited in the claim beyond the abstract idea? No
In step 2B, the claims are analyzed to determine whether any additional element, or combination of additional elements, are sufficient to ensure that the claims amount to significantly more than the judicial exception. This analysis is also termed a search for an “inventive concept.” An “inventive concept” is furnished by an element or combination of elements that is recited in the claim in addition to (beyond) the judicial exception, and is sufficient to ensure that the claim as a whole amount to significantly more than the judicial exception itself. Alice Corp., 573 U.S. at 27-18, 110 USPQ2d at 1981 (citing Mayo, 566 U.S. at 72-73, 101 USPQ2d at 1966). As discussed above in “Step 2A – Prong Two”, the identified additional elements in independent claims 1, 10, and 12 and dependent claims 2-9, 11, and 13-20 are equivalent to adding the words “apply it” on a generic computer, and/or generally link the use of the judicial exception to a particular technological environment or field of use. Therefore, the claims as a whole do not amount to significantly more than the judicial exception itself.
Viewing the additional limitations in combination also shows that they fail to ensure the claims amount to significantly more than the abstract idea. When considered as an ordered combination, the additional components of the claims add nothing that is not already present when considered separately, and thus simply append the abstract idea with words equivalent to “apply it” on a generic computer and/or mere instructions to implement the abstract idea on a generic computer or/and append the abstract idea with insignificant extra solution activity associated with the implementation of the judicial exception, (e.g., mere data gathering, post-solution activity) and/or simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception.
Dependent claims 2-9, 11, and 13-20 fail to include any additional elements. In other words, each of the limitations/elements recited in respective independent claims are further part of the abstract idea as identified by the Examiner for each respective dependent claim (i.e. they are part of the abstract idea recited in each respective claim).
The Examiner has therefore determined that no additional element, or combination of additional claims elements are sufficient to ensure the claims amount to significantly more than the abstract idea identified above. Therefore, claims 1-20 are not eligible subject matter under 35 USC 101.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
Determining the scope and contents of the prior art.
Ascertaining the differences between the prior art and the claims at issue.
Resolving the level of ordinary skill in the pertinent art.
Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable under US 20250029488 A1 (“Zahid”) in view of US 20140309879 A1 (“Ricci”).
In regards to claim 1, Zahid discloses the following limitations with the exception of the underlined limitations.
An assistance system comprising ([0107], “an Advanced Driver Assistance System (ADAS) leverages … applications for … safety and user-responsive functionality”): a memory storing instructions that ([0136], “instruction … may be stored in memory”), when executed by a processor ([0003], “a system … includes … a … processor”), cause the processor to: acquire a driving suggestion from an assisting operator associated with a driving scenario involving a vehicle ([0100], “the driving assist … suggests … paths to the driver”);
receive a driving command and vocal data from the vehicle about following the driving suggestion during the driving scenario;
and train a shared-driving model using the driving suggestion, the driving command, and the vocal data ([0113], “Machine learning models … could adjust … driving style”).
Ricci discloses
receive a driving command ([0107], “Embodiments include a method for … the vehicle control system receiving an audible command”) and vocal data from the vehicle about following the driving suggestion during the driving scenario ([0324], “sensors may … receive input … through voice data”);
Zahid and Ricci are considered analogous to the claimed invention because they are in the field of vehicle control applications, systems, and methods. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the applicant’s invention for an assistance system comprising: a memory storing instructions that, when executed by a processor, cause the processor to: acquire a driving suggestion from an assisting operator associated with a driving scenario involving a vehicle; and train a shared-driving model using the driving suggestion, the driving command, and the vocal data, as disclosed by Zahid, receive a driving command and vocal data from the vehicle about following the driving suggestion during the driving scenario, as disclosed by Ricci, to provide an audible command, sensors, and voice data for methods and systems that accept inputs into a vehicle to control functions of the vehicle. One skilled in the art would recognize and value the addition of an audible command, sensors, and voice data for methods and systems that accept inputs into a vehicle to control functions of the vehicle.
In regards to claim 2, Zahid discloses
wherein the instructions to receive the driving command further include instructions to: communicate a dataset labeled automatically without manual annotation ([0133], “a vehicle … may receive … statements determined by the application based on a set of data, such as an instruction”) for feedback about the driving suggestion, the vocal data, and the driving command ([0066], “data received … may … provide feedback”), and the dataset includes information from a questionnaire about the feedback ([0081], “the … application … may be providing … answers to questions”) and the dataset forms training data for the shared-driving model ([0220], “an artifact … generates predictions by finding patterns in … training data sets”).
In regards to claim 3, Zahid discloses the following limitations with the exception of the underlined limitation.
further including instructions to: control the vehicle using the driving suggestion directly during a time step associated with a maneuver for the driving scenario;
upon an operator of the vehicle resisting the driving suggestion with a steering command, increase a strength value for haptic feedback corresponding with the driving suggestion for the maneuver ([0104], “the system reliably detects or predicts unsafe driving conditions … The AI system … is trained … to recognize patterns indicating potential hazards … Upon determining an unsafe condition, the vehicle … transmits an alert … This alert may take various forms: auditory … or haptic”);
and communicate a label for the steering command and the maneuver without supervision ([0103], “When an unsafe driving condition is predicted, the monitoring application can communicate directly”), the label having tokens representing the steering command and the maneuver ([0337], “If the driver … is showing progress, they might earn … badges or points”).
Ricci discloses
further including instructions to: control the vehicle using the driving suggestion directly during a time step associated with a maneuver for the driving scenario ([0495], “The vehicle control system … may … wait a period of time, in step 1836”);
Zahid and Ricci are considered analogous to the claimed invention because they are in the field of vehicle control applications, systems, and methods. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the applicant’s invention for an assistance system comprising: a memory storing instructions that, when executed by a processor, cause the processor to: acquire a driving suggestion from an assisting operator associated with a driving scenario involving a vehicle; and train a shared-driving model using the driving suggestion, the driving command, and the vocal data, upon an operator of the vehicle resisting the driving suggestion with a steering command, increase a strength value for haptic feedback corresponding with the driving suggestion for the maneuver; and communicate a label for the steering command and the maneuver without supervision, the label having tokens representing the steering command and the maneuver, as disclosed by Zahid, receive a driving command and vocal data from the vehicle about following the driving suggestion during the driving scenario, further including instructions to: control the vehicle using the driving suggestion directly during a time step associated with a maneuver for the driving scenario, as disclosed by Ricci, to provide an audible command, sensors, and voice data for methods and systems that accept inputs into a vehicle to control functions of the vehicle. One skilled in the art would recognize and value the addition of an audible command, sensors, and voice data for methods and systems that accept inputs into a vehicle to control functions of the vehicle.
In regards to claim 4, Zahid discloses
wherein the operator overrides the haptic feedback and the driving suggestion ([0127], “The generated prompt is … conveyed to the occupant, utilizing the vehicle's … haptic feedback mechanisms”).
In regards to claim 5, Zahid discloses
wherein a large language model (LLM) generates the driving suggestion to navigate a maneuver using a steering command and a pedal command that are verbal ([0113], “Machine learning models can optimize … functionality, learning from historical data and real-time inputs to improve … suggestions”).
In regards to claim 6, Zahid does not disclose wherein the driving command is a blend of an operator command and one of a steering command, a braking command, and an accelerator command associated with the driving suggestion.
Ricci discloses
wherein the driving command is a blend of an operator command and one of a steering command, a braking command, and an accelerator command associated with the driving suggestion ([0573], “the function control module … may send … commands … to change the functions of the vehicle … The changes may include gesture preferences, vehicles settings, infotainment system controls, climate control settings, access and manipulation of the dashboard, console functions or layouts, or one or more vehicles subsystems”).
Zahid and Ricci are considered analogous to the claimed invention because they are in the field of vehicle control applications, systems, and methods. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the applicant’s invention for an assistance system comprising: a memory storing instructions that, when executed by a processor, cause the processor to: acquire a driving suggestion from an assisting operator associated with a driving scenario involving a vehicle; and train a shared-driving model using the driving suggestion, the driving command, and the vocal data, as disclosed by Zahid, receive a driving command and vocal data from the vehicle about following the driving suggestion during the driving scenario, wherein the driving command is a blend of an operator command and one of a steering command, a braking command, and an accelerator command associated with the driving suggestion, as disclosed by Ricci, to provide an audible command, sensors, voice data, and a function control module for methods and systems that accept inputs into a vehicle to control functions of the vehicle. One skilled in the art would recognize and value the addition of an audible command, sensors, voice data, and a function control module for methods and systems that accept inputs into a vehicle to control functions of the vehicle.
In regards to claim 7, Zahid discloses
wherein: the assisting operator is one of co-located and remote from the vehicle ([0267], “module may communicate with a remote server to keys of new vehicles, users, etc., and the like”);
the assisting operator is one of a human ([0102], “threshold … could be set based on … human drivers”) and a robot ([0244], “vehicle … may … navigate without human input”);
and the vehicle is one of a simulated vehicle, an online vehicle, a driving simulator, a test vehicle, and a field vehicle ([0244], “The vehicle ... may be a self-propelled wheeled conveyance ... vehicle ... may be an electric vehicle, a hybrid vehicle, a hydrogen fuel cell vehicle, a plug-in hybrid vehicle, or any other type of vehicle with a fuel cell stack, a motor, and/or a generator” Examiner notes that a simulated vehicle, an online vehicle, a driving simulator, or a test vehicle can include a fuel cell stack, an electric motor, and/or a generator in their modeled systems.).
In regards to claim 8, Zahid discloses
wherein the shared-driving model is one of a model prediction control (MPC) system, a data-driven system that is trained, an automated driving system (ADS), a shared-decision making (SDM) model, a neural network (NN), and a learning model using a factorization machine (FM) ([0225], “the models may include artificial intelligence (AI) models, machine learning models, neural networks, or the like” Examiner notes that Model Predictive Control (MPC), data-driven systems, Automated Driving Systems (ADS), Shared Decision-Making (SDM) models, Neural Networks (NN), and learning models using Factorization Machines (FM)—are considered forms of machine intelligence models.).
In regards to claim 9, Zahid discloses the following limitations with the exception of the underlined limitations.
wherein: the driving suggestion is one of a steering command, a braking command, an acceleration command, a voice command, and a labeled explanation about a maneuver during the driving scenario ([0133], “a vehicle … may receive … statements determined by the application based on a set of data, such as an instruction”);
the driving command is one of the steering command, the braking command, and the acceleration command;
the vocal data and the driving command represent reactions to the driving suggestion;
and the vehicle is one of an automobile, a simulated vehicle, a virtual vehicle, a train, an airplane, and a boat ([0244], “vehicle ... may be ... a car, a sports utility vehicle, a truck, a bus, a van, ... any other type of vehicle with a fuel cell stack, a motor, and/or a generator. Other ... vehicles include ... trains, planes, boats”).
Ricci discloses
wherein: the driving suggestion is one of a steering command, a braking command, an acceleration command, a voice command ([0573], “the function control module … may send … commands … to change the functions of the vehicle … The changes may include gesture preferences, vehicles settings, infotainment system controls, climate control settings, access and manipulation of the dashboard, console functions or layouts, or one or more vehicles subsystems”),
the driving command is one of the steering command, the braking command, and the acceleration command ([0573], “the function control module … may send … commands … to change the functions of the vehicle … The changes may include gesture preferences, vehicles settings, infotainment system controls, climate control settings, access and manipulation of the dashboard, console functions or layouts, or one or more vehicles subsystems”);
the vocal data and the driving command represent reactions to the driving suggestion ([0324], “sensors may … receive input … through voice data”);
Zahid and Ricci are considered analogous to the claimed invention because they are in the field of vehicle control applications, systems, and methods. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the applicant’s invention for an assistance system comprising: a memory storing instructions that, when executed by a processor, cause the processor to: acquire a driving suggestion from an assisting operator associated with a driving scenario involving a vehicle; and train a shared-driving model using the driving suggestion, the driving command, and the vocal data, and a labeled explanation about a maneuver during the driving scenario; and the vehicle is one of an automobile, a simulated vehicle, a virtual vehicle, a train, an airplane, and a boat, as disclosed by Zahid, receive a driving command and vocal data from the vehicle about following the driving suggestion during the driving scenario, wherein: the driving suggestion is one of a steering command, a braking command, an acceleration command, a voice command, the driving command is one of the steering command, the braking command, and the acceleration command; the vocal data and the driving command represent reactions to the driving suggestion; as disclosed by Ricci, to provide an audible command, sensors, voice data, and a function control module for methods and systems that accept inputs into a vehicle to control functions of the vehicle. One skilled in the art would recognize and value the addition of an audible command, sensors, voice data, and a function control module for methods and systems that accept inputs into a vehicle to control functions of the vehicle.
In regards to claim 10, Zahid discloses the following limitations with the exception of the underlined limitations.
A non-transitory computer-readable medium comprising (([0062], “The computer-readable storage medium may be … a non-transitory computer readable storage medium”): instructions that ([0136], “instruction … may be stored in memory”), when executed by a processor ([0003], “a system … includes … a … processor”), cause the processor to: acquire a driving suggestion from an assisting operator associated with a driving scenario involving a vehicle ([0100], “the driving assist … suggests … paths to the driver”);
receive a driving command and vocal data from the vehicle about following the driving suggestion during the driving scenario;
and train a shared-driving model using the driving suggestion, the driving command, and the vocal data ([0113], “Machine learning models … could adjust … driving style”).
Ricci discloses
receive a driving command ([0107], “Embodiments include a method for … the vehicle control system receiving an audible command”) and vocal data from the vehicle about following the driving suggestion during the driving scenario ([0324], “sensors may … receive input … through voice data”);
Zahid and Ricci are considered analogous to the claimed invention because they are in the field of vehicle control applications, systems, and methods. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the applicant’s invention for a non-transitory computer-readable medium comprising: instructions that, when executed by a processor, cause the processor to: acquire a driving suggestion from an assisting operator associated with a driving scenario involving a vehicle; and train a shared-driving model using the driving suggestion, the driving command, and the vocal data, as disclosed by Zahid, receive a driving command and vocal data from the vehicle about following the driving suggestion during the driving scenario, as disclosed by Ricci, to provide an audible command, sensors, and voice data for methods and systems that accept inputs into a vehicle to control functions of the vehicle. One skilled in the art would recognize and value the addition of an audible command, sensors, and voice data for methods and systems that accept inputs into a vehicle to control functions of the vehicle.
In regards to claim 11, Zahid discloses
wherein the instructions to receive the driving command further include instructions to: communicate a dataset labeled automatically without manual annotation ([0133], “a vehicle … may receive … statements determined by the application based on a set of data, such as an instruction”) for feedback about the driving suggestion, the vocal data, and the driving command ([0066], “data received … may … provide feedback”), and the dataset includes information from a questionnaire about the feedback ([0081], “the … application … may be providing … answers to questions”) and the dataset forms training data for the shared-driving model ([0220], “an artifact … generates predictions by finding patterns in … training data sets”).
In regards to claim 12, Zahid discloses the following limitations with the exception of the underlined limitations.
A method comprising: acquiring a driving suggestion from an assisting operator associated with a driving scenario involving a vehicle ([0100], “the driving assist … suggests … paths to the driver”);
receive a driving command and vocal data from the vehicle about following the driving suggestion during the driving scenario;
and train a shared-driving model using the driving suggestion, the driving command, and the vocal data ([0113], “Machine learning models … could adjust … driving style”).
Ricci discloses
receive a driving command ([0107], “Embodiments include a method for … the vehicle control system receiving an audible command”) and vocal data from the vehicle about following the driving suggestion during the driving scenario ([0324], “sensors may … receive input … through voice data”);
Zahid and Ricci are considered analogous to the claimed invention because they are in the field of vehicle control applications, systems, and methods. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the applicant’s invention for a method comprising: acquiring a driving suggestion from an assisting operator associated with a driving scenario involving a vehicle; and train a shared-driving model using the driving suggestion, the driving command, and the vocal data, as disclosed by Zahid, receiving a driving command and vocal data from the vehicle about following the driving suggestion during the driving scenario, as disclosed by Ricci, to provide an audible command, sensors, and voice data for methods and systems that accept inputs into a vehicle to control functions of the vehicle. One skilled in the art would recognize and value the addition of an audible command, sensors, and voice data for methods and systems that accept inputs into a vehicle to control functions of the vehicle.
In regards to claim 13, Zahid discloses
wherein receiving the driving command further includes: communicating a dataset labeled automatically without manual annotation ([0133], “a vehicle … may receive … statements determined by the application based on a set of data, such as an instruction”) for feedback about the driving suggestion, the vocal data, and the driving command ([0066], “data received … may … provide feedback”), and the dataset includes information from a questionnaire about the feedback ([0081], “the … application … may be providing … answers to questions”) and the dataset forms training data for the shared-driving model ([0220], “an artifact … generates predictions by finding patterns in … training data sets”).
In regards to claim 14, Zahid discloses the following limitations with the exception of the underlined limitation.
further comprising: controlling the vehicle using the driving suggestion directly during a time step associated with a maneuver for the driving scenario;
upon an operator of the vehicle resisting the driving suggestion with a steering command, increase a strength value for haptic feedback corresponding with the driving suggestion for the maneuver ([0104], “the system reliably detects or predicts unsafe driving conditions … The AI system … is trained … to recognize patterns indicating potential hazards … Upon determining an unsafe condition, the vehicle … transmits an alert … This alert may take various forms: auditory … or haptic”);
and communicating a label for the steering command and the maneuver without supervision ([0103], “When an unsafe driving condition is predicted, the monitoring application can communicate directly”), the label having tokens representing the steering command and the maneuver ([0337], “If the driver … is showing progress, they might earn … badges or points”).
Ricci discloses
further comprising: controlling the vehicle using the driving suggestion directly during a time step associated with a maneuver for the driving scenario ([0495], “The vehicle control system … may … wait a period of time, in step 1836”);
Zahid and Ricci are considered analogous to the claimed invention because they are in the field of vehicle control applications, systems, and methods. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the applicant’s invention for a method comprising: acquiring a driving suggestion from an assisting operator associated with a driving scenario involving a vehicle; and train a shared-driving model using the driving suggestion, the driving command, and the vocal data, upon an operator of the vehicle resisting the driving suggestion with a steering command, increase a strength value for haptic feedback corresponding with the driving suggestion for the maneuver; and communicating a label for the steering command and the maneuver without supervision, the label having tokens representing the steering command and the maneuver, as disclosed by Zahid, receiving a driving command and vocal data from the vehicle about following the driving suggestion during the driving scenario, further comprising: controlling the vehicle using the driving suggestion directly during a time step associated with a maneuver for the driving scenario, as disclosed by Ricci, to provide an audible command, sensors, and voice data for methods and systems that accept inputs into a vehicle to control functions of the vehicle. One skilled in the art would recognize and value the addition of an audible command, sensors, and voice data for methods and systems that accept inputs into a vehicle to control functions of the vehicle.
In regards to claim 15, Zahid discloses
wherein the operator overrides the haptic feedback and the driving suggestion ([0127], “The generated prompt is … conveyed to the occupant, utilizing the vehicle's … haptic feedback mechanisms”).
In regards to claim 16, Zahid discloses
wherein a large language model (LLM) generates the driving suggestion to navigate a maneuver using a steering command and a pedal command that are verbal ([0113], “Machine learning models can optimize … functionality, learning from historical data and real-time inputs to improve … suggestions”).
In regards to claim 17, Zahid does not disclose wherein the driving command is a blend of an operator command and one of a steering command, a braking command, and an accelerator command associated with the driving suggestion.
Ricci discloses
wherein the driving command is a blend of an operator command and one of a steering command, a braking command, and an accelerator command associated with the driving suggestion ([0573], “the function control module … may send … commands … to change the functions of the vehicle … The changes may include gesture preferences, vehicles settings, infotainment system controls, climate control settings, access and manipulation of the dashboard, console functions or layouts, or one or more vehicles subsystems”).
Zahid and Ricci are considered analogous to the claimed invention because they are in the field of vehicle control applications, systems, and methods. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the applicant’s invention for a method comprising: acquiring a driving suggestion from an assisting operator associated with a driving scenario involving a vehicle; and training a shared-driving model using the driving suggestion, the driving command, and the vocal data, as disclosed by Zahid, receiving a driving command and vocal data from the vehicle about following the driving suggestion during the driving scenario, wherein the driving command is a blend of an operator command and one of a steering command, a braking command, and an accelerator command associated with the driving suggestion, as disclosed by Ricci, to provide an audible command, sensors, voice data, and a function control module for methods and systems that accept inputs into a vehicle to control functions of the vehicle. One skilled in the art would recognize and value the addition of an audible command, sensors, voice data, and a function control module for methods and systems that accept inputs into a vehicle to control functions of the vehicle.
In regards to claim 18, Zahid discloses
wherein: the assisting operator is one of co-located and remote from the vehicle ([0267], “module may communicate with a remote server to keys of new vehicles, users, etc., and the like”);
the assisting operator is one of a human ([0102], “threshold … could be set based on … human drivers”) and a robot ([0244], “vehicle … may … navigate without human input”);
and the vehicle is one of a simulated vehicle, an online vehicle, a driving simulator, a test vehicle, and a field vehicle ([0244], “The vehicle ... may be a self-propelled wheeled conveyance ... vehicle ... may be an electric vehicle, a hybrid vehicle, a hydrogen fuel cell vehicle, a plug-in hybrid vehicle, or any other type of vehicle with a fuel cell stack, a motor, and/or a generator” Examiner notes that a simulated vehicle, an online vehicle, a driving simulator, or a test vehicle can include a fuel cell stack, an electric motor, and/or a generator in their modeled systems.).
In regards to claim 19, Zahid discloses
wherein the shared-driving model is one of a model prediction control (MPC) system, a data-driven system that is trained, an automated driving system (ADS), a shared-decision making (SDM) model, a neural network (NN), and a learning model using a factorization machine (FM) ([0225], “the models may include artificial intelligence (AI) models, machine learning models, neural networks, or the like” Examiner notes that Model Predictive Control (MPC), data-driven systems, Automated Driving Systems (ADS), Shared Decision-Making (SDM) models, Neural Networks (NN), and learning models using Factorization Machines (FM)—are considered forms of machine intelligence models.).
In regards to claim 20, Zahid discloses the following limitations with the exception of the underlined limitations.
wherein: the driving suggestion is one of a steering command, a braking command, an acceleration command, a voice command, and a labeled explanation about a maneuver during the driving scenario ([0133], “a vehicle … may receive … statements determined by the application based on a set of data, such as an instruction”);
the driving command is one of the steering command, the braking command, and the acceleration command;
the vocal data and the driving command represent reactions to the driving suggestion;
and the vehicle is one of an automobile, a simulated vehicle, a virtual vehicle, a train, an airplane, and a boat ([0244], “vehicle ... may be ... a car, a sports utility vehicle, a truck, a bus, a van, ... any other type of vehicle with a fuel cell stack, a motor, and/or a generator. Other ... vehicles include ... trains, planes, boats”).
Ricci discloses
wherein: the driving suggestion is one of a steering command, a braking command, an acceleration command, a voice command ([0573], “the function control module … may send … commands … to change the functions of the vehicle … The changes may include gesture preferences, vehicles settings, infotainment system controls, climate control settings, access and manipulation of the dashboard, console functions or layouts, or one or more vehicles subsystems”),
the driving command is one of the steering command, the braking command, and the acceleration command ([0573], “the function control module … may send … commands … to change the functions of the vehicle … The changes may include gesture preferences, vehicles settings, infotainment system controls, climate control settings, access and manipulation of the dashboard, console functions or layouts, or one or more vehicles subsystems”);
the vocal data and the driving command represent reactions to the driving suggestion ([0324], “sensors may … receive input … through voice data”);
Zahid and Ricci are considered analogous to the claimed invention because they are in the field of vehicle control applications, systems, and methods. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the applicant’s invention for a method comprising: acquiring a driving suggestion from an assisting operator associated with a driving scenario involving a vehicle; and training a shared-driving model using the driving suggestion, the driving command, and the vocal data, and a labeled explanation about a maneuver during the driving scenario; and the vehicle is one of an automobile, a simulated vehicle, a virtual vehicle, a train, an airplane, and a boat, as disclosed by Zahid, receiving a driving command and vocal data from the vehicle about following the driving suggestion during the driving scenario, wherein: the driving suggestion is one of a steering command, a braking command, an acceleration command, a voice command, the driving command is one of the steering command, the braking command, and the acceleration command; the vocal data and the driving command represent reactions to the driving suggestion; as disclosed by Ricci, to provide an audible command, sensors, voice data, and a function control module for methods and systems that accept inputs into a vehicle to control functions of the vehicle. One skilled in the art would recognize and value the addition of an audible command, sensors, voice data, and a function control module for methods and systems that accept inputs into a vehicle to control functions of the vehicle.
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Any inquiry concerning this communication or earlier communications from the
examiner should be directed to Lisa Antoine whose telephone number is
(571) 272-4252 and whose email address is lantoine@uspto.gov. The examiner can be reached Monday-Thursday, 7:30 am-5:30 pm CT. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Xuan Thai, can be reached on (571) 272-7147. The fax phone number for the organization where this application or proceeding is assigned is (571) 273-8300.
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/LISA H ANTOINE/
Examiner, Art Unit 3715
/XUAN M THAI/Supervisory Patent Examiner, Art Unit 3715
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