A method is disclosed for analyzing historical accident information to adjust driving actions of an autonomous vehicle over a travel route in order to avoid accidents which have occurred over the travel route. Historical accident information for the travel route can be analyzed to, for example, determine accident types which occurred over the travel route and determine causes and/or probable causes of the accident types. In response to determining accident types and causes/probable causes of the accident types over the travel route, adjustments can be made to the driving actions planned for the autonomous vehicle over the travel route. In addition, in an embodiment, historical accident information can be used to analyze available travel routes and select a route which presents less risk of accident than others.

A method for changing a control authority of an autonomous vehicle in consideration of an external environment includes determining a first risk level of a physical condition of a driver who drives the autonomous vehicle, determining a second risk level in response to one of a mental condition or a conscious condition of the driver, determining a driver proficiency level of a driver, and allocating a control authority of the autonomous vehicle to the driver or to the autonomous vehicle according to a result of a determination of the first risk level, the second risk level, and the driver proficiency level.

A mobile object control method including: recognizing physical objects near a mobile object and a route shape; generating a target trajectory based on a result of the recognition and cause the mobile object to travel autonomously along the target trajectory; and determining that an abnormality has occurred in a control system for causing the mobile object to travel autonomously by performing the recognition when a time period from a timing when a degree of deviation between a reference target trajectory determined by the route shape and serving as a reference for generating the target trajectory and a position of the mobile object is greater than or equal to a predetermined degree to a timing when the degree of deviation is less than the predetermined degree is greater than or equal to a first predetermined time period and output a determination result.

A vehicle includes a processing device that detects an authentication device approaching the vehicle, determines a user's impaired state based on user condition information acquired using at least one device mounted on the vehicle, and performs a safe driving assistance service. The safe driving assistance service can prevent an impaired user from operating the vehicle.

In one or more embodiments, a method comprises receiving, at a processor, an input signal from an input device in response to a first actuation of the input device by a driver of an autonomous vehicle. The input device is a device disposed with the autonomous vehicle and has a second actuation of the input device associated with a standard operation of the input device. The second actuation has an actuation pattern different from an actuation pattern of the first actuation. In response to the input signal, a determination is made by the processor to determine whether the autonomous vehicle can perform a maneuver safely. In response to determining that the autonomous vehicle can perform the maneuver safely, a signal is sent by the processor to cause the autonomous vehicle to perform the maneuver.

A method for operating a vehicle, which can be operated in a manual and an automated driving mode is provided. Depending on a driving situation occurring in the automated driving mode, a take-over request for a user of the vehicle to take over a driving task is issued to the vehicle user. During the automated driving mode the vehicle monitors whether the vehicle user is able to comply with the take-over request at the time of the issued take-over request based on a current seat position of the vehicle user and/or a current seat setting of a vehicle seat of the vehicle user.

An environmental information acquiring unit (11) to acquire environmental information on an environment around a mobile object, an action information acquiring unit (12) to acquire action information on an action of a driver of the mobile object, a calculation unit (13) to obtain control information for performing automated driving control of the mobile object on the basis of the environmental information acquired by the environmental information acquiring unit (11) and a machine learning model (18) that uses the environmental information as an input and outputs the control information, a contribution information determining unit (14) to determine contribution information having a high degree of contribution to the control information on the basis of the environmental information and the control information, a cognitive information calculating unit (15) to calculate cognitive information indicating a cognitive region of the driver in the environment around the mobile object on the basis of the action information and the environmental information, a specification unit (16) to specify unrecognized contribution information estimated not to be recognized by the driver on the basis of the contribution information and the cognitive information, and an information output control unit (17) to output driving assistance information necessary for driving assistance on the basis of the unrecognized contribution information specified by the specification unit (16) are provided.

A vehicle motion control apparatus includes a control unit which controls a steering apparatus and a brake apparatus provided in a vehicle. The control unit acquires a normative motion state amount necessary for the vehicle to trace a target traveling path, acquires a target motion state amount necessary for generating a yaw moment to cancel unstable behavior of the vehicle, and acquires a target steering angle for generating a steering angle moment and a target brake force for generating a brake moment, to obtain a necessary yaw moment generated by the vehicle. The control unit outputs a first control command for obtaining the target steering angle to the steering apparatus and outputs a second control command for obtaining the target brake force to the brake apparatus.

A method for controlling autonomous driving in a vehicle capable of the autonomous driving may include collecting vehicle travel status information and system status information during the autonomous driving, sensing a failure based on the system status information, identifying normally controllable actuators when sensing the failure, determining a risk degree corresponding to the sensed failure based on the normally controllable actuator information and the vehicle travel status information, determining a safety state based on normally controllable actuator information and the risk degree, and determining a failure safety strategy corresponding to the safety state.

A map management system stores map information used by an automated driving vehicle. The automated driving vehicle detects an obstacle based on the map information, or acquires a margin distance when stopping in front of an obstacle based on the map information. When requiring a remote operator's decision about an action with respect to the obstacle, the automated driving vehicle issues a support request that requests the remote operator to give support. The map management system acquires an operator instruction to the automated driving vehicle issued by the remote operator in response to the support request. The map management system estimates a type of the obstacle based on a state of acquisition of the operator instruction or a content of the operator instruction. Then, the map management system updates the map information according to the type of the obstacle.