A method for controlling autonomous driving in an autonomous vehicle includes detecting a situation in which autonomous driving is impossible while the vehicle operates in an autonomous driving mode, outputting a control-right handover request warning alarm and then activating a minimal risk maneuver driving mode, determining a human driver gaze validity based on the detected situation, determining a human driver intervention validity upon determination that the human driver gaze is valid, and determining control-right handover of the autonomous vehicle based on the human driver intervention validity. Thus, the control-right may be reliably transferred from a system to a human driver.

Provided is a vehicle control device configured to: recognize a surrounding situation of a vehicle; control steering and acceleration/deceleration of the vehicle; detect operation states of a plurality of external recognition sensors; determine a driving mode of the vehicle as any one of a plurality of driving modes including a first driving mode, a second driving mode, and a third driving mode; change the third driving mode to either one of the first driving mode and the second driving mode when determining that a failure has occurred in one of the plurality of external recognition sensors that implement: a function of causing the vehicle to follow a preceding vehicle; and a function of assisting the vehicle in keeping a lane; and change the third driving mode to the second driving mode when determining that degradation in performance has occurred in one of the plurality of external recognition sensors.

A vehicle control device includes a recognition unit configured to recognize a position and a surrounding situation of a vehicle, a driving control unit configured to control steering and acceleration/deceleration of the vehicle independently of an operation of a driver of the vehicle, and a mode determination unit configured to determine any one of a plurality of driving modes including a first driving mode and a second driving mode as a driving mode of the vehicle and change the driving mode of the vehicle to a driving mode in which a task is severer when a task associated with the determined driving mode is not executed by the driver, the second driving mode being a driving mode in which a task imposed on the driver is milder than that in the first driving mode. When accuracy of recognition of the position of the vehicle is lowered, the mode determination unit estimates a speed at which the vehicle travels on a road on the basis of curvature of the road in front of the vehicle and changes the driving mode of the vehicle when the estimated speed exceeds a predetermined prescribed speed.

A method for the self-check of at least one driving function of an autonomous or semi-autonomous vehicle in vehicle operation, after an error message about the at least one driving function, in which in one step, at least one vehicle electronic system and/or at least one sensor is/are restarted, a check is made for a further appearance of the error message after each restart, and in the event an error message is not repeated after the restart, the driving function in question is checked during operation of the autonomous or semi-autonomous vehicle.

Technologies and techniques for operating an assistance system of a motor vehicle for providing a shoulder function. Under a first condition, a motor vehicle is detected on a shoulder of a roadway via at least one detecting apparatus in accordance with at least one predetermined first criterion. Under a second condition, a steering behavior of a driver of the motor vehicle is determined in accordance with a second criterion, where a shoulder function is executed in accordance with which an automatic driving intervention. Under a third condition, an obstacle ahead of the motor vehicle in the direction of travel is detected by the at least one detecting apparatus in accordance with a specified third criterion, where a control signal influencing the execution of the shoulder function is output.

Techniques for determining a location of a vehicle in an environment using sensors and determining calibration information associated with the sensors are discussed herein. A vehicle can use map data to traverse an environment. The map data can include semantic map objects such as traffic lights, lane markings, etc. The vehicle can use a sensor, such as an image sensor, to capture sensor data. Semantic map objects can be projected into the sensor data and matched with object(s) in the sensor data. Such semantic objects can be represented as a center point and covariance data. A distance or likelihood associated with the projected semantic map object and the sensed object can be optimized to determine a location of the vehicle. Sensed objects can be determined to be the same based on matching with the semantic map object. Epipolar geometry can be used to determine if sensors are capturing consistent data.

An arithmetic operation device for automobiles includes an arithmetic element state detection unit that detects a parameter indicating a state of an arithmetic element, an external device detection unit that detects a use state of a device that affects the parameter, and a mode selection unit that selects one of a normal mode in which both a basic traveling function unit that can execute control related to a basic traveling function and an automatic driving function unit that can execute control related to an automatic driving function and a degeneration mode in which only the basic traveling function unit is operated, and the mode selection unit selects the degeneration mode when the parameter exceeds a threshold or when it is predicted that the parameter exceeds the threshold.

An approach is provided for computing an estimated time of arrival via a route based on a degraded state of a vehicle after an accident and/or malfunction. The approach involves receiving, by one or more processors, data indicating an operational status of a vehicle. The approach also involves processing, by the one or more processors, the data to determine a degraded operational state of the vehicle. The approach further involves computing, by the one or more processors, an estimated time of arrival, a route, or a combination thereof of the vehicle based on the degraded operational state.

Wrong way travel detection and control systems and methods for a vehicle utilize a set of perception sensor systems each configured to perceive a position of the vehicle relative to its environment, a map system configured to maintain map data, and a controller configured to receive first information from the set of perception sensor systems and the map system, generate a confidence score indicative of a likelihood that the vehicle is traveling in a wrong direction along a roadway using a vehicle position model and the received first information, compare the confidence score to a set of one or more thresholds, and based on the comparing, selectively control one or more operating parameters of the vehicle to remedy the wrong direction travel of the vehicle.

Localization error handling using output is described. A computing system associated with a vehicle can receive sensor data from a sensor associated with vehicle. The computing system can determine, based at least partly on the sensor data, a first instruction for controlling the vehicle during a first period of time and a difference in pose information associated with a pose of the vehicle. Based at least partly on determining the difference, the computing system can retrieve a second instruction for controlling the vehicle during a second period of time prior to the first period of time and, based at least partly on comparing the first instruction and the second instruction, the computing system can determine whether the vehicle is to follow the first instruction or perform an alternate operation.