# US 2026/0097782 A1 · Systems and methods for training a learning model using labeled data generated with an assisting operator for a task > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2026/0097782 A1 - Document ID: US20260097782A1 - Status: Published application - Kind: A1 - Application number: 18/905,603 - Filed: 2024-10-03 - Published: 2026-04-09 - Earliest claimed: 2024-10-03 - Assignees: Toyota Research Institute, Inc.; Toyota Jidosha Kabushiki Kaisha - Applicants: Toyota Research Institute, Inc. - Inventors: Jonathan A. DeCastro; Emily Sarah Sumner; Deepak Edakkattil Gopinath; Andrew Michael Silva; Thomas M. Balch; Xiongyi Cui; Guy Rosman - Web page: https://patentgrep.com/patent/US20260097782A1 ## CPC - B60W 60/001: {Planning or execution of driving tasks} - B60W 10/04: including control of propulsion units - B60W 10/18: including control of braking systems - B60W 10/20: including control of steering systems - B60W 50/16: Tactile feedback to the driver, e.g. vibration or force feedback to the driver on the steering wheel or the accelerator pedal - G06F 30/27: using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model - B60W: CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract Systems, methods, and other embodiments described herein relate to training a learning model using labeled data generated through a suggestion from an assisting operator to another operator for executing a task. In one embodiment, a method includes acquiring a driving suggestion from an assisting operator associated with a driving scenario involving a vehicle. The method also includes receiving a driving command and vocal data from the vehicle about following the driving suggestion during the driving scenario. The method also includes training a shared-driving model using the driving suggestion, the driving command, and the vocal data. ## Claims ### Claim 1 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. ### Claim 2 (depends on 1) The assistance system of claim 1, wherein the instructions to receive the driving command further include instructions to: communicate a dataset labeled automatically without manual annotation for feedback about the driving suggestion, the vocal data, and the driving command, and the dataset includes information from a questionnaire about the feedback and the dataset forms training data for the shared-driving model. ### Claim 3 (depends on 1) The assistance system of claim 1 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; and communicate a label for the steering command and the maneuver without supervision, the label having tokens representing the steering command and the maneuver. ### Claim 4 (depends on 3) The assistance system of claim 3, wherein the operator overrides the haptic feedback and the driving suggestion. ### Claim 5 (depends on 1) The assistance system of claim 1, 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. ### Claim 6 (depends on 1) The assistance system of claim 1, 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. ### Claim 7 (depends on 1) The assistance system of claim 1, wherein: the assisting operator is one of co-located and remote from the vehicle; the assisting operator is one of a human and a robot; and the vehicle is one of a simulated vehicle, an online vehicle, a driving simulator, a test vehicle, and a field vehicle. ### Claim 8 (depends on 1) The assistance system of claim 1, 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). ### Claim 9 (depends on 1) The assistance system of claim 1, 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; 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. ### Claim 10 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; 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. ### Claim 11 (depends on 10) The non-transitory computer-readable medium of claim 10, wherein the instructions to receive the driving command further include instructions to: communicate a dataset labeled automatically without manual annotation for feedback about the driving suggestion, the vocal data, and the driving command, and the dataset includes information from a questionnaire about the feedback and the dataset forms training data for the shared-driving model. ### Claim 12 A method comprising: acquiring a driving suggestion from an assisting operator associated with a driving scenario involving a vehicle; receiving a driving command and vocal data from the vehicle about following the driving suggestion during the driving scenario; and training a shared-driving model using the driving suggestion, the driving command, and the vocal data. ### Claim 13 (depends on 12) The method of claim 12, wherein receiving the driving command further includes: communicating a dataset labeled automatically without manual annotation for feedback about the driving suggestion, the vocal data, and the driving command, and the dataset includes information from a questionnaire about the feedback and the dataset forms training data for the shared-driving model. ### Claim 14 (depends on 12) The method of claim 12 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, increasing 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. ### Claim 15 (depends on 14) The method of claim 14, wherein the operator overrides the haptic feedback and the driving suggestion. ### Claim 16 (depends on 12) The method of claim 12, 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. ### Claim 17 (depends on 12) The method of claim 12, 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. ### Claim 18 (depends on 12) The method of claim 12, wherein: the assisting operator is one of co-located and remote from the vehicle; the assisting operator is one of a human and a robot; and the vehicle is one of a simulated vehicle, an online vehicle, a driving simulator, a test vehicle, and a field vehicle. ### Claim 19 (depends on 12) The method of claim 12, 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). ### Claim 20 (depends on 12) The method of claim 12, 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; 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.