Traveling environment information is recognized. A predicted traveling path is calculated based on a driving condition of a vehicle. An oncoming-vehicle predicted traveling path is calculated based on behavior of an oncoming vehicle. It is determined whether the vehicle has an intention to enter a first intersecting road at an intersection. When the vehicle cannot enter the first intersecting road, the predicted traveling path is corrected to a limit traveling path. It is determined whether the oncoming vehicle has an intention to enter a second intersecting road at the intersection. When the oncoming vehicle cannot enter the second intersecting road, the oncoming-vehicle predicted traveling path is corrected to an oncoming-vehicle limit traveling path. The oncoming vehicle is set as a control target against which emergency braking is executed when the predicted traveling path and the oncoming-vehicle predicted traveling path overlap each other at least in part.

The disclosure relates to a vehicle control method. The vehicle control method includes: receiving a motion parameter of a vehicle; detecting, based on the motion parameter, whether there is a longitudinal obstacle in front of the vehicle; and when it is detected that there is a longitudinal obstacle in front of the vehicle, generating compensation torque based on the detected longitudinal obstacle, to perform compensation for control torque of the vehicle to generate required torque of the vehicle. The disclosure further relates to a vehicle control device, a computer-readable storage medium, and a vehicle.

Techniques are provided for autonomous vehicle fleet management for reduced traffic congestion. A request is received for a vehicular ride. The request includes an initial spatiotemporal location and a destination spatiotemporal location. A processor is used to generate a representation of lane segments. Each lane segment is weighted in accordance with a number of other vehicles on the lane segment. A vehicle located within a threshold distance to the initial spatiotemporal location is identified such that the identified vehicle has at least one vacant seat. The processor is used to determine a route for operating the identified vehicle from the initial spatiotemporal location to the destination spatiotemporal location. The route includes one or more lane segments of the lane segments. An aggregate of weights of the one or more lane segments is below a threshold value. The received request and the determined route are transmitted to the identified vehicle.

A method for carrying out a start-up process of an at least semi-automated vehicle. The method includes: recognizing at least one unsuccessful start-up process using a first set of drive parameters; reporting the unsuccessful start-up process to a control system; receiving changed driving-related boundary conditions from the control system; ascertaining at least one changed drive parameter from the changed driving-related boundary conditions; and repeating the start-up process at least once, using the at least one changed drive parameter.

A vehicle control system may include a controller that obtains route information based on a driving route and a location of a vehicle, searches for an uneven road surface on the driving route based on the route information, calculates an impulse based on vehicle information and shape information about the found uneven road surface when the uneven road surface is found, and sets a target speed based on the calculated impulse and user data.

We disclose adaptive active safety systems which utilize a sensing system to detect road conditions and actuate an active safety routine based thereon. One disclosed method includes transmitting, with a multispectral LIDAR system on a vehicle, a multispectral light beam directed at an anticipated region of travel of the vehicle within a road, and analyzing a response, of a photodetector, to a return of the multispectral light beam. The method also includes determining, based on the analyzing of the response, a hazardous surface condition in the anticipated region of travel of the vehicle, and actuating, based on the determination of the hazardous surface condition, an active safety routine. The method can be executed by an ADAS in which the determinations of the hazardous surface conditions on the road in the anticipated region of travel are executed in real time to thereby produce a road aware ADAS.

A method of determining a traveling state of a vehicle, such as passing over a speed bump, occurrence of wheel slip, or traveling on a slope, is determined in real time to prevent degradations in wheel slip control performance and to avoid unnecessarily malfunctions in a traction control system without compromise of wheel slip control performance. The method includes steps of: determining a torque command of a drive unit to apply torque to a drive wheel in accordance with vehicle driving information collected during traveling of the vehicle; determining an acceleration error in accordance with the determined torque command and information regarding a measured longitudinal acceleration of the vehicle measured by a first sensor; determining an acceleration disturbance rate in accordance with the determined torque command; and determining a current traveling state of the vehicle in accordance with the determined acceleration error and the determined acceleration disturbance rate.

Techniques for estimating a height range of an object in an environment are discussed herein. For example, a sensor, such as a lidar sensor, can capture three-dimensional data of an environment. The sensor data can be associated with a two-dimensional representation. A ground surface can be removed from the sensor data, and clustering techniques can be used to cluster remaining sensor data provided in a two-dimensional representation to determine object(s) represented therein. A height of a sensor object can be represented as a first height based on an extent of the sensor data associated with the object and can be represented as a second height based on beam spreading aspects of the sensor data and/or sensor data associated with additional objects. Thus, a minimum and/or maximum height of an object can be determined in a robust manner. Such height ranges can be used to control an autonomous vehicle.

Aspects of the disclosure relate to controlling a vehicle in an autonomous driving mode where vehicle has a drive by wire braking system. For instance, while the vehicle is being controlled in the autonomous driving mode, a signal corresponding to input at a brake pedal of the drive by wire braking system may be received. An amount of braking may be determined based on the received signal. The amount of braking may be used to determine a trajectory for the vehicle to follow. The vehicle may be controlled in the autonomous driving mode using the trajectory.

A vehicle control device is mountable on a vehicle. The vehicle control device includes: a processor; and a memory storing instructions that, when executed by the processor, cause the vehicle control device to perform operations. The operations includes: acquiring detection information obtained by detecting an obstacle around the vehicle; performing collision determination of evaluating a possibility of collision with the obstacle, generating, based on the detection information, information on an approaching object that is an obstacle approaching the vehicle and information on a detection point group that is a set of detection points indicating an obstacle that does not move; and excluding the approaching object from collision determination in a case in which the detection point group has a shielding effect of shielding the vehicle from the approaching object. The shielding effect is evaluated by using a gap threshold that is set based on a vehicle width.