Disclosed in the present disclosure are a method and an apparatus for determining a vehicle speed control model training sample. The method includes: a lane in map data is divided into a first lane area and a second lane area, and to-be-measured vehicle speed control features indicated by the two lane areas are different; the to-be-measured vehicle speed control features are determined as target vehicle speed control feature when a difference between a first empirical highest vehicle speed distribution and a second empirical highest vehicle speed distribution is greater than or equal to a preset difference threshold; and starting coordinates and ending coordinates of each preset lane section in the map data, and the target vehicle speed control features and a vehicle speed control label in the preset lane section are taken as a vehicle speed control model training sample.

Disclosed are a device and a method for controlling a driving mode of a vehicle. The device includes a sensor for collecting information about an access road to a controlled-access highway, and a controller which determines a switching point on the access road at which the driving mode of the vehicle is switched to a sport mode, based on the information about the access road to the controlled-access highway, and switches the driving mode of the vehicle to the sport mode when the vehicle reaches the switching point on the access road. Thus, the vehicle accesses the controlled-access highway naturally without interfering with flow of other vehicles.

Provided herein is a method for assisting a driver with driving a motor vehicle. The method includes ascertaining a permissible driving speed in a route section by evaluating environmental data describing the motor vehicle environment. The method further includes calculating a target maximum speed, which is lower than the permissible driving speed, by subtracting a predefined reduction amount from the permissible driving speed and/or by multiplying the permissible driving speed by a predefined scaling factor. The method further includes controlling at least one alert device for outputting an alert to the driver when a present driving speed of the motor vehicle exceeds the target maximum speed and/or controlling the driving speed of the motor vehicle by a longitudinally guiding driver assistance system, wherein the target maximum speed is used as a maximum speed or as a target speed.

A method for the automatic control of the longitudinal dynamics of a vehicle is provided by which vehicles traveling ahead are detected. If an upcoming traffic jam is detected, the vehicle is decelerated until a predefined distance behind the tail end of the traffic jam is reached. When the predefined distance from the traffic jam tail end has been reached, the vehicle automatically controlled in its longitudinal dynamics is able to close the remaining, predefined distance to the traffic jam tail end at a low differential velocity in comparison to the velocity of the traffic jam tail end. Using an additional rear sensor system that senses trailing vehicles, the controlled vehicle is made to close the distance to the traffic jam tail end only if a trailing vehicle was detected.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for monitoring a dedicated roadway the runs in parallel to a railroad. In some implementations, a system includes a central server, an interface, and sensors. The interface receives data from a railroad system that manages the railroad parallel to the dedicated roadway. The sensors are positioned in a fixed location relative to the dedicated roadway. Each sensor can detect vehicles in a first field of view on the dedicated roadway. For each detected vehicle, each sensor can generate sensor data based on the detected vehicle in the dedicated roadway and the data received at the interface. Each sensor can generate observational data and instruct the detected vehicle to switch to an enhanced processing mode. Each sensor can determine an action for the detected vehicle to take based on the generated observational data.

A vehicle control apparatus includes a recognizer which is configured to recognize a surrounding environment of a host vehicle and a driving controller which is configured to perform automated driving on the basis of a recognition result of the recognizer, wherein the driving controller is configured to perform passing control of causing the host vehicle to pass a preceding vehicle if at least one of a first condition according to a relative speed of the host vehicle with respect to the preceding vehicle and a second condition according to a type of the preceding vehicle is satisfied when the recognizer recognizes the preceding vehicle, and is configured to curb the passing control by changing at least one of the first condition and the second condition when a continuity of a first route on which the host vehicle is traveling decreases.

The present disclosure provides a method for identifying a confidence level of an autonomous driving system in an autonomous driving vehicle. The method includes determining hardware currently used by the autonomous driving system to realize required functions and environmental factors which affect the hardware capability of the hardware, and establishing a relationship between the hardware capability and the environmental factors; based on environmental factors on a future specific road section acquired in real time, calculating a degree to which the hardware capability will be affected on the specific road section; in consideration of acquired the environmental factors, judging an influence of the affected hardware capability on the realization of required functions of the autonomous driving system based on the acquired the environmental factors; and reflecting the influence on the realization of required functions of the autonomous driving system as a confidence level, and prompting the confidence level to a driver.

Autonomous driving of a vehicle in which computerized perception by the vehicle, including of its environment and of itself (e.g., its egomotion), is used to autonomously drive the vehicle and, additionally, can also be used to provide feedback to enhance performance, safety, and/or other attributes of autonomous driving of the vehicle (e.g., when certain conditions affecting the vehicle are determined to exist by detecting patterns in or otherwise analyzing what is perceived by the vehicle), such as by adjusting autonomous driving of the vehicle, conveying messages regarding the vehicle, and/or performing other actions concerning the vehicle.

Disclosed are a vehicle capable of controlling acceleration in consideration of a driving environment and an acceleration limit control method therefor. The acceleration limit control method of the disclosure includes determining a base value of an acceleration limit level, which is classified into a plurality of levels, determining a first correction value based on manipulation of an accelerator pedal, determining a second correction value based on a driving environment, determining a final acceleration limit level by applying the first correction value and the second correction value to the base value, and determining a limit acceleration based on the final acceleration limit level.

A method for automated control of a vehicle includes automatically navigating a vehicle within a current lane of travel with a driving assistance system, and predetermining a steering maneuver during the automatic navigation with the driving assistance system. The method also includes, prior to performing the predetermined steering maneuver, biasing the vehicle within the current lane of travel with an offset from a center of the current lane of travel using the driving assistance system, the offset in a direction of the predetermined steering maneuver, and performing the predetermined steering maneuver with the driving assistance system.