A non-transitory computer-readable medium storing instructions, the instructions, when executed by a processor, cause the processor to: perform a follow-up steering control for changing a steering angle of a vehicle in such a manner that the vehicle travels along a target traveling line determined based on a preceding vehicle trajectory, which is a travel trajectory of a preceding vehicle traveling ahead of the vehicle; and when a first distance condition and a manual steering condition are both satisfied while the follow-up steering control is being performed, stop the follow-up steering control, the first distance condition being a condition satisfied when a deviation distance in a road-width direction between the preceding vehicle trajectory and the vehicle is equal to or longer than a predetermined first threshold, and the manual steering condition being a condition satisfied when a driver operates a steering wheel to change a position in the road-width direction.

A steering-angle control apparatus controls a steering mechanism based on a state command value, which is input in each predetermined period. An interpolation unit interpolates between a previous value and a current value of the input state command value to compute a state interpolation value in an interpolation period, which is shorter than the predetermined period. An interpolation-value determination unit determines whether the state interpolation value is an abnormal value. A control unit controls the steering mechanism based on the state interpolation value computed by the interpolation unit when the interpolation-value determination unit determines that the state interpolation value is not an abnormal value, and controls the steering mechanism based on the current value of the state command value when the interpolation-value determination unit determines that the state interpolation value is an abnormal value.

Aspects of the disclosure provide for the evaluation of a scheduling system software for managing autonomous vehicle scheduling and dispatching. For instance, a problem condition for a simulation may be identified. The simulation may be run using the identified problem condition. The simulation may include a plurality of simulated autonomous vehicles each utilizing its own autonomous vehicle control software and map information common to each simulated autonomous vehicle. The problem condition may relate to a particular simulated autonomous vehicle of the plurality. Output of the simulation may be analyzed to determine a score for the scheduling system software. The scheduling system software may be evaluated using the score.

Examples relating to vehicle velocity calculation using radar technology are described. An example method performed by a computing system may involve, while a vehicle is moving on a road, receiving, from two or more radar sensors mounted at different locations on the vehicle, radar data representative of an environment of the vehicle. The method may involve, based on the data, detecting at least one scatterer in the environment. The method may involve making a determination of a likelihood that the at least one scatterer is stationary with respect to the vehicle. The method may involve, based on the determination being that the likelihood is at least equal to a predefined confidence threshold, calculating a velocity of the vehicle based on the data from the sensors. The calculated velocity may include an angular and linear velocity. Further, the method may involve controlling the vehicle based on the calculated velocity.

A vehicle control system installed on a vehicle includes: an automatic steering control device configured to execute automatic steering control that determines a steering angle command value and controls steering of the vehicle such that an actual steering angle follows the steering angle command value; a stop state detection device configured to detect a stop state where the vehicle is stopped; and an override detection device configured to detect an override operation by a driver of the vehicle. When the override operation is detected in the stop state, the automatic steering control device prohibits variation in the actual steering angle due to the automatic steering control, until the vehicle starts moving.

A vehicle guidance system detects when a driver of the vehicle manually intervenes in the longitudinal and/or transverse guidance of the vehicle while the vehicle is being operated in an automated driving mode. The vehicle guidance system outputs an indication to the driver via a user interface of the vehicle prompting the driver to take over the longitudinal and/or transverse guidance of the vehicle. The vehicle guidance system also continues to provide the longitudinal and/or lateral guidance of the vehicle in at least a partially automated manner for a takeover period of time and/or for a takeover distance.

A vehicle steering control device includes a control device. The control device is configured to control a steering reaction force to be applied to a steering operation performed by a driver of a driver's vehicle, acquire information on a curved road ahead of the driver's vehicle in a traveling direction, set a guide steering operation amount based on the information on the curved road, predict a time at which the driver starts an actual steering operation for driving the driver's vehicle along the curved road as a steering operation start time, and set, based on a difference between the guide steering operation amount and an actual amount of the steering operation, the steering reaction force at a time earlier by a predetermined period than the steering operation start time.

Systems and methods are provided herein for operating an electric vehicle in a vehicle yaw mode. The electric vehicle includes a normal driving mode where the electric vehicle is steered by turning the steerable wheels (e.g., left or right) and vehicle yaw mode where the vehicle controls the torque applied to each wheel. In response to receiving input to initiate vehicle yaw mode and yaw direction, the system determines the inner wheels and the outer wheels and provides forward torque to the outer wheels of the vehicle and backward torque to the inner wheels of the vehicle to rotate the vehicle.

The present disclosure provides a method and a device for autonomous driving control, a vehicle, a storage medium and an electronic device. The method includes: obtaining first actual position data of a first vehicle body; obtaining relative position data between a second vehicle body and the first vehicle body; determining second actual position data of the second vehicle body according to the first actual position data and the relative position data, so that the vehicle performs autonomous driving control according to the first and second actual position data. The method can obtain the relative position between two vehicle bodies connected in the non-rigid manner and the real-time positions of the two vehicle bodies under different driving conditions in real time during the driving, can accurately depict the dynamic characteristics of two vehicle bodies, so that the vehicle performs autonomous driving control according to the first and second actual position data.

Systems and methods to control a radar system to perform cross-traffic management in a vehicle with a trailer involve determining a location of the trailer behind the vehicle, and adjusting an initial field of view of the radar system to a modified field of view that excludes the location of the trailer. One or more other vehicles are detected with the radar system having the modified field of view. A cross-traffic alert is implemented based on the detecting the one or more other vehicles.