A method for adjusting the speed of a vehicle (EGO) moving with an initial speed to a target speed, including: determining a control profile comprising at least one control profile part, in which the control profile includes at least one control parameter for the vehicle (EGO) and allowing the vehicle (EGO) to change its speed from the initial speed to the target speed, and adjusting the speed of the vehicle (EGO) according to the control profile. A further method is disclosed for leading a vehicle (EGO) that is moving on a lane into a target position with respect to at least one other vehicle, in which the method is used to adjust the speed of the vehicle (EGO) to reach the target position. Also described are a related device, a system, a vehicle, a computer program product and a storage medium.

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.

An automated driving system (ADS) includes an automation control module for controlling one or more driving functions of a vehicle, and a safety control module for determining one or more operating conditions relevant to the safety performance of the vehicle, such as driver awareness and processor temperature. The automation control module is configured to automatically adjust the speed of the vehicle based on the one or more operating conditions determined by the safety control module.

Aspects of the disclosure relate to generating a speed plan for an autonomous vehicle. As an example, the vehicle is maneuvered in an autonomous driving mode along a route using pre-stored map information. This information identifies a plurality of keep clear regions where the vehicle should not stop but can drive through in the autonomous driving mode. Each keep clear region of the plurality of keep clear regions is associated with a priority value. A subset of the plurality of keep clear regions is identified based on the route. A speed plan for stopping the vehicle is generated based on the priority values associated with the keep clear regions of the subset. The speed plan identifies a location for stopping the vehicle. The speed plan is used to stop the vehicle in the location.

Disclosed herein is a control apparatus and method for improving fuel efficiency in a CACC system, which can improve fuel efficiency through control of a vehicle speed so that a vehicle travels using an optimized cost in consideration of a target vehicle speed, current vehicle speed, minimum driving speed set in the vehicle, and a deceleration distance if the vehicle that uses the CACC system senses a forward vehicle and enters into a CACC active mode. The control method for improving fuel efficiency in a CACC system includes setting a target speed profile based on a target speed of the subject vehicle and an expected driving path, determining whether a target vehicle to be followed by the subject vehicle exists, and controlling the driving speed of the subject vehicle according to the set target speed profile depending on whether or not the target vehicle exists.

A method ensures that a vehicle can safely pass a traffic light. The vehicle includes a processor and a light sensor. The method includes receiving traffic data, establishing a speed profile, establishing a control distance, the processor establishing, in accordance with the speed profile, a control distance at which braking ensures that the vehicle stops safely before the position of the traffic light, adjustment according to the speed profile, detecting the state of the traffic light when the vehicle is at the control distance from the traffic light, and the processor activating braking if the traffic light is red.

A vehicular control system determines a planned path of travel for a vehicle along a traffic lane in which the vehicle is traveling on a road. The system determines a respective target speed for waypoints along the planned path that represents a speed the vehicle should travel when passing through the respective waypoint. The system determines a speed profile for the vehicle to travel at as the vehicle travels along the planned path, with at least two different speeds being based on a difference in target speeds of at least two consecutive respective waypoints of the plurality of waypoints. The system determines an acceleration profile for the vehicle to follow as it changes from one speed to another speed of the speed profile. The system controls the vehicle to maneuver the vehicle along the planned path in accordance with the determined speed and acceleration profiles.

Among other things, we describe techniques for estimating a speed profile for a proposed trajectory for a vehicle and operating the vehicle along the proposed trajectory according to the speed profile, including a method for: obtaining, by a planning circuit on a vehicle, a proposed trajectory for the vehicle in response to a driving scenario; obtaining, by the planning circuit, an estimated speed profile, and a confidence score, wherein the confidence score represents a similarity of the estimated speed profile to an actual speed profile that would be generated by a control circuit for the proposed trajectory; determining whether the confidence score meets a confidence threshold; and in accordance with a determination that the confidence score exceeds the confidence threshold, operating, by a control circuit on the vehicle, the vehicle along the proposed trajectory.

A driving control device mounted on a vehicle includes a processor. The processor is configured to create a speed profile. The processor is configured to approximate the speed profile by a predetermined approximate model and estimate a predicted amount of regenerative energy based on an approximation result. The processor is configured to set, based on the predicted amount of regenerative energy, a first region and a second region in the approximation result as a region in which the vehicle travels using an electric motor, the first region being a region from a timing of starting of the vehicle until first time has elapsed from the timing of starting of the vehicle, and the second region being a region from a timing of deceleration of the vehicle until second time has elapsed from the timing of deceleration of 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.