An energy-optimal vehicle control system for at least one vehicle including a roadway data source configured for providing traffic and map data including at least one drive segment of the at least one vehicle, and an electrical processing system operably coupled with the roadway data source. The electrical processing system includes an optimizer for generating an energy-optimal speed profile for the at least one drive segment, and the electrical processing system is configured for controlling the speed of the at least one vehicle in accordance with the energy-optimal speed profile.

A vehicle control device (1) includes an automated driving control unit (100) configured to execute automated driving of a vehicle and an acquisition unit (124) configured to acquire movement states in a running direction and a lateral direction of the vehicle. The automated driving control unit is configured to execute the automated driving such that the movement states which have been acquired by the acquisition unit before the automated driving has been started are maintained in a predetermined time or a predetermined distance when automated driving has been started by switching from manual driving.

The vehicle control device includes a start determination unit configured to determine whether or not the inter-vehicle distance between the preceding vehicle and the host vehicle has become equal to or greater than a start threshold greater in value than the stop threshold, and a vehicle control unit configured to start the host vehicle based on a preset speed profile after the start determination unit determines that the inter-vehicle distance between the preceding vehicle and the host vehicle is equal to or greater than the start threshold and maintain the stopped state of the host vehicle until the start determination unit determines that the inter-vehicle distance between the preceding vehicle and the host vehicle is equal to or greater than the start threshold after the preceding vehicle and the host vehicle stop.

To minimize a pedal operation of a driver and to provide convenience of driving by flexibly controlling a maximum creep speed during a creep driving in a traffic congestion section, a vehicle includes: a radar configured to obtain speed information of a preceding vehicle and distance information to the preceding vehicle; a sensor configured to acquire behavior information of the vehicle; a controller configured to determine whether or not the vehicle has entered the traffic congestion section based on the behavior information of the vehicle, to determine a safety distance and a surplus distance related to the preceding vehicle, to determine a maximum creep speed and a creep torque based on the surplus distance, and to control operation of at least one of a motor or an engine to transmit the creep torque to a wheel of the vehicle.

A method is intended to regulate the speed of an at least partially self-driving vehicle, knowing the radius of curvature of a future position it is preparing to take on a course along which it is travelling. This method comprises a step (10-90) in which the speed is regulated as a function of a speed set point and, if a radius of curvature of the future position which is representative of a curve is detected, a phase of deceleration down to a chosen speed followed by a phase of acceleration until the speed setpoint is obtained are imposed on the vehicle. In this step (10-90), when the driver imposes acceleration on his vehicle during the deceleration phase, this deceleration phase is halted and then another phase of acceleration until the speed set point is obtained is imposed on the vehicle.

Generally, the present disclosure is directed to systems and methods that include or otherwise leverage an iterative solver as part of optimizing a motion plan for an autonomous vehicle (AV). In particular, a scenario generator within a motion planning system can include a warm start generator configured to determine an initial trajectory that respects the dynamics of the autonomous vehicle and that closely tracks a speed profile determined by a constraint solver and one or more nominal paths determined by a route selector. A decision validator can analyze speed profiles and nominal paths to identify potential inconsistencies and validate a decision before optimization and execution. An initial trajectory can be further optimized by an iterative solver to determine an optimized trajectory for execution as a motion plan for the autonomous vehicle.

A vehicle control method is provided. In the method, a target driving speed and an actual driving speed of the vehicle are obtained. A control mode among candidate control modes is determined by the processing circuitry based on a comparison between the target driving speed and the actual driving speed. The candidate control modes includes a braking control mode, an acceleration control mode, and a stopping control mode. A throttle amount and a braking amount to change the actual driving speed to the target driving speed are determined by the processing circuitry. Further, the determined throttle amount and braking amount are applied to the vehicle based on the determined control mode.

A traveling control apparatus is mounted on a vehicle that includes an electric motor and an internal combustion engine as power sources. The traveling control apparatus includes an electronic control unit configured to create a speed profile obtained by predicting speed of the vehicle at each time, derive, based on at least the speed profile, a coefficient profile that is a coefficient at each time used at the time of predicting an amount of regenerative energy recoverable by regenerative braking of the electric motor, approximate the speed profile with a predetermined approximation model and estimate a predicted amount of regenerative energy based on an approximation result and the coefficient profile, and determine the power source used for traveling based on the predicted amount of regenerative energy.

A method includes detecting, via a processor of an autonomous vehicle, an upcoming downhill road segment of a route on which the autonomous vehicle is currently travelling. The detection is based on map data, camera data, and/or inertial measurement unit (IMU) data. In response to detecting the upcoming downhill road segment, a descent plan is generated for the autonomous vehicle. The descent plan includes a speed profile and a brake usage plan. The brake usage plan specifies a non-zero amount of retarder usage and an amount of foundation brake usage for a predefined time period. The method also includes autonomously controlling the autonomous vehicle, based on the descent plan, while the autonomous vehicle descends the downhill road segment.

A method for controlling a coasting guide function is provided. The method may include: detecting a speed limit and an average speed of a peripheral vehicle; detecting a valid speed limit when a coasting event occurs; and calculating a target speed by using a speed factor computed by using at least one of the valid speed limit, the average speed of the peripheral vehicle, or a current speed.