A device may receive vehicle operation data associated with operation of a plurality of vehicles, and may process the vehicle operation data to generate processed vehicle operation data. The device may extract multiple features from the processed vehicle operation data, and may train machine learning models, with the multiple features, to generate trained machine learning models that provide model outputs. The device may process the multiple features, with a feature selection model and based on the model outputs, to select sets of features from the plurality of features, and may process the sets of features, with the trained machine learning models, to generate indications of driving behavior and reliabilities of the indications. The device may select a set of features, from the sets of features, based on the indications and the reliabilities, where the set of features may be calculated by a device associated with a particular vehicle.

An override conciliating portion executes processing to conciliate an override request during an execution of automated driving control (i.e., override conciliation processing). In the override conciliation processing, it is determined whether or not there is the override request (step S20). If the determination result of the step S20 is positive, it is determined whether or not a second automated driving mode is selected as an operation mode (step S21). If the determination result of the step S21 is negative, acceptance processing of the override request is executed (step S22). If the determination result of the step S21 is positive, invalidation processing of the override request is executed (step S23).

The vehicle includes an operation switch for manually operating the operation state of the accessories. The vehicle control system includes a first controller that performs an evacuation traveling in response to a decrease in the driver's consciousness level, and a second controller that controls an operation state of the accessories based on a request from the first controller or operation information of the operation switch. The first controller is configured to transmit, to the second controller, a specific operation rejection request for performing a specific operation rejection process of rejecting the control of the accessories based on the specific operation of the operation switch in response to a decrease in the driver's consciousness level. The second controller is configured to perform the specific operation rejection process when the specific operation rejection request is received from the first controller.

The vehicle includes an operation switch for manually operating the operation state of the accessories. The vehicle control system includes a first controller that performs an evacuation traveling in response to a decrease in the driver's consciousness level, and a second controller that controls an operation state of the accessories based on a request from the first controller or operation information of the operation switch. The first controller is configured to transmit, to the second controller, a specific operation rejection request for performing a specific operation rejection process of rejecting the control of the accessories based on the specific operation of the operation switch in response to a decrease in the driver's consciousness level. The second controller is configured to perform the specific operation rejection process when the specific operation rejection request is received from the first controller.

According to certain aspects, a computer-implemented method for operating an autonomous or semi-autonomous vehicle may be provided. With the customer's permission, an identity of a vehicle operator may be identified and a vehicle operator profile may be retrieved. Operating data regarding autonomous operation features operating the vehicle may be received from vehicle-mounted sensors. When a request to disable an autonomous feature is received, a risk level for the autonomous feature is determined and compared with a driver behavior setting for the autonomous feature stored in the vehicle operator profile. Based upon the risk level comparison, the autonomous vehicle retains control of vehicle or the autonomous feature is disengaged depending upon which is the safer driver—the autonomous vehicle or the vehicle human occupant. As a result, unsafe disengagement of self-driving functionality for autonomous vehicles may be alleviated. Insurance discounts may be provided for autonomous vehicles having this safety functionality.

In a number of illustrative variations, an always-on motion controller may include a path planner system; a driver monitoring system, and a motion controller system. The always-on motion controller may provide for an always present autonomous driving system which may seamlessly take control of the vehicle where driver attention is lost, distracted, or momentarily absent. The always-on motion controller may seamlessly release control of the vehicle to the driver or driver attention is regained.

The driving force ECU calculates a restricted driving force for a driving force restricting control, by using a Proportional-Integral-Differential control formula which utilizes a difference between a target acceleration varied depending on a vehicle speed and an actual acceleration of the vehicle. The driving force ECU adjusts (changes) a proportion gain K1 of the Proportional-Integral-Differential control formula based on an inclination angle θ of a road in such a manner that a value of the proportion gain K1 used when the inclination inclination angle θ is relatively large is smaller than a value of the proportion gain K1 used when the inclination inclination angle θ is relatively small. The driving force ECU performs a driving force restricting control by selecting, as a target driving force used for the driving force restricting control, a pedal required driving force or the restricted driving force, whichever is smaller.

Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having one or more autonomous or semi-autonomous operation features are provided. According to certain aspects, the operating status and/or configuration of autonomous operation features of an autonomous or semi-autonomous vehicle may be determined, such as via an on-board computer system or mobile device, and/or then directly or indirectly wirelessly communicated via data transmission from the vehicle computer system or mobile device to a remote server. An adjustment to one or more risk levels associated with operation of the autonomous or semi-autonomous vehicle may also be determined, and an auto insurance policy, premium, or discount may be adjusted based upon the adjustment to the risk levels and presented to the customer for their review and approval. As a result, insurance cost savings may be passed onto risk averse customers that opt into to a rewards program.

Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having one or more autonomous or semi-autonomous operation features are provided. According to certain aspects, the operating status of the features, the identity of a vehicle operator, risk levels for operation of the vehicle by the vehicle operator, or damage to the vehicle may be determined based upon sensor or other data. According to further aspects, decisions regarding transferring control between the features and the vehicle operator may be made based upon sensor data and information regarding the vehicle operator. Additional aspects may recommend or install updates to the autonomous operation features based upon determined risk levels. Some aspects may include monitoring transportation infrastructure and communicating information about the infrastructure to vehicles.

An embodiment of the invention provides a method to control a mechanical system based on the cognitive state of a user, where a first action is performed at an input device that is associated with the user. The cognitive state of the user is detected at the input device; and, a change to the first action is determined based on the cognitive state of the user. A controlled action is performed based on the recommended change. A system can include an input device associated with user, where a first action is performed at the input device. A processor connected to the input device detects the cognitive state of the user at the input device and determines a change to the first action based on the cognitive state of the user. A controller connected to the processor performs a controlled action based on the recommended change.