The task management device includes a control unit that performs maintenance start control for starting maintenance of the internal environment of the vehicle during a period in which the vehicle operated in the mode corresponding to the application is operated in the first mode, and performs mode switching control for switching the vehicle to the second mode different from the first mode after the maintenance is completed.

Methods and systems for determining risk associated with operation of autonomous vehicles using autonomous communication are provided. According to certain aspects, autonomous operation features associated with a vehicle may be determined, including features associated with autonomous communication between vehicles or with infrastructure. This information may be used to determine risk levels for a plurality of features, which may be based upon test data regarding the features or actual loss data. Expected use levels and autonomous communication levels may further be determined and used with the risk levels to determine a total risk level associated with operation of the vehicle. The autonomous communication levels may indicate the types of communications, the levels of communication with other vehicles or infrastructure, or the frequency of autonomous communication. The total risk level may be used to determine or adjust aspects of an insurance policy associated with the vehicle.

Aspects of the disclosure relate generally to detecting discrete actions by traveling vehicles. The features described improve the safety, use, driver experience, and performance of autonomously controlled vehicles by performing a behavior analysis on mobile objects in the vicinity of an autonomous vehicle. Specifically, an autonomous vehicle is capable of detecting and tracking nearby vehicles and is able to determine when these nearby vehicles have performed actions of interest by comparing their tracked movements with map data.

A method, medium, and apparatus for educating and reducing risk to inexperienced drivers using vehicles with autonomous navigation systems. Data regarding a driver's past experience with vehicles and operating environments may be used to proactively warn the driver about a potential danger detected or predicted by the vehicle. An autonomous vehicle may prevent the driver from operating the vehicle under unfamiliar circumstances or from causing a collision. Data regarding a driver's past experience with vehicles and the safety features thereof may be used to mitigate risk of injury or property damage by selectively activating safety features in a new vehicle which the driver has not previously driven. Data regarding a driver's past experience with vehicles and safety features thereof may be used to determine a decreased or increased rental rate for a particular vehicle.

A vehicle control apparatus that controls a vehicle based on peripheral information of the vehicle, comprising: a first operator used to start first travel control; a second operator used to resume the first travel control after the first travel control has been terminated; a third operator used to further start second travel control during the first travel control; and a control unit configured to, while the first travel control and the second travel control are active, if the first travel control and the second travel control are terminated based on the same condition or the same timing, resume the first travel control and the second travel control in accordance with an operation of the second operator.

Methods and systems for determining fault for an accident involving a vehicle having one or more autonomous (and/or semi-autonomous) operation features and paying claims associated with such accidents are provided. According to certain aspects, operating data from sensors within or near the vehicle may be used to determine the occurrence of a vehicle accident, such as a collision. The operating data may further be used to determine an allocation of fault for the accident between a vehicle operator, the autonomous operation features, or a third party. The allocation of fault may be used to further determine and make claims payments related to the accident. In some embodiments, claims may be rejected based upon the operating data and determined allocation of fault.

A computer-implemented method, system, and/or computer program product controls a driving mode of a self-driving vehicle (SDV). One or more processors compare a control processor competence level of an on-board SDV control processor in controlling the SDV to a human driver competence level of a human driver in controlling the SDV while the SDV encounters a current roadway condition which is a result of current weather conditions of the roadway on which the SDV is currently traveling. One or more processors then selectively assign control of the SDV to the SDV control processor or to the human driver while the SDV encounters the current roadway condition based on which of the control processor competence level and the human driver competence level is relatively higher to one another.

Systems and methods for controlling an autonomous vehicle are provided. In one example embodiment, a computer-implemented method includes receiving data indicative of an operating mode of the vehicle, wherein the vehicle is configured to operate in a plurality of operating modes. The method includes determining one or more response characteristics of the vehicle based at least in part on the operating mode of the vehicle, each response characteristic indicating how the vehicle responds to a potential collision. The method includes controlling the vehicle based at least in part on the one or more response characteristics.

Provided is a vehicle travel control apparatus configured to set an operation mode of automatic start control to any one of a first mode, in which the automatic start control is executed, and a second mode, in which the automatic start control is not executed, the vehicle travel control apparatus being further configured to: issue to a driver a notification for inquiring whether the driver desires the automatic start control to be executed when the current travel state of an own vehicle is a specific state; and set the operation mode of the automatic start control to the first mode when the driver has performed a predetermined response operation in response to the notification.

Models can be generated of a vehicle's view of its environment and used to maneuver the vehicle. This view need not include what objects or features the vehicle is actually seeing, but rather those areas that the vehicle is able to observe using its sensors if the sensors were completely un-occluded. For example, for each of a plurality of sensors of the object detection component, a computer may generate an individual 3D model of that sensor's field of view. Weather information is received and used to adjust one or more of the models. After this adjusting, the models may be aggregated into a comprehensive 3D model. The comprehensive model may be combined with detailed map information indicating the probability of detecting objects at different locations. The model of the vehicle's environment may be computed based on the combined comprehensive 3D model and detailed map information.