A system for maneuvering a vehicle has a detection system, a prediction system, and a vehicle control system. The detection system is configured to detect a nearby vehicle adjacent to the vehicle. The prediction system is configured to calculate a predicted trajectory of the nearby vehicle upon receiving a detection result from the detection system. The vehicle control system is configured to maneuver the vehicle based on the predicted trajectory upon receiving a control signal from the prediction system. The vehicle control system maneuvers the vehicle to keep a specified distance away from the nearby vehicle. A method for maneuvering a vehicle includes detecting a nearby vehicle adjacent to the vehicle, calculating a predicted trajectory of the nearby vehicle, and maneuvering the vehicle based on the predicted trajectory to keep a specified distance away from the nearby vehicle.

The systems and methods described herein disclose detecting obstacles in a vehicular environment using host vehicle input and associated trust levels. As described here, measured vehicles, either manual or autonomous, that detect an obstacle in the environment will operate to respond to the obstacle. As such, those movements can be used to determine if an obstacle exists in the environment, even if the obstacle cannot be detected directly. The systems and methods can include a host vehicle receiving prediction data about an evasive behavior from one or more measured vehicles in a vehicular environment. A trust level can then be established for the measured vehicles. An obscured obstacle can be determined using the evasive behavior and the trust level which can then be mapped in the vehicular environment. A guidance input can then be created for the host vehicle using the obscured obstacle and the trust level.

A non-transitory computer readable storage medium has instructions executed by a processor to obtain the relative speed between a first traffic object and a second traffic object. The separation distance between the first traffic object and the second traffic object is received. The relative speed and the separation distance are combined to form a quantitative measure of hazard encountered by the first traffic object. The obtain, receive and combine operations are repeated to form cumulative measures of hazard associated with the first traffic object. The cumulative measures of hazard are analyzed to derive a first traffic object safety score for the first traffic object.

A method of improving a merging efficiency of an ego vehicle is described. The method includes determining one or more merge gaps between vehicles in a target lane of a multilane highway. The method also includes computing an exposure time in which the ego vehicle is specified to merge into the one or more merge gaps. The method further includes selecting a merge gap between a first vehicle and a second vehicle in the target lane of the multilane highway having a maximum exposure time.

Embodiments of the present disclosure disclose a method and apparatus for avoidance control of a vehicle, an electronic device, and a storage medium, where the method includes: obtaining behavior information of a moving obstacle, where the moving obstacle is located in a direction of movement of the vehicle and a distance between the moving obstacle and the vehicle satisfies a preset avoidance distance; determining an avoidance strategy for the vehicle based on the behavior information of the moving obstacle; and controlling movement of the vehicle based on the avoidance strategy. The method in the embodiments of the present disclosure considers the behavior information of the moving obstacle in the process of avoidance control of the vehicle, and the vehicle can be controlled to travel when the moving obstacle takes an avoidance action, thereby improving the accuracy of avoidance for the vehicle and the practicality of intelligent driving.

An automotive electronic dynamics control system for an automated motor-vehicle. The electronic dynamics control system is designed to implement two distinct Model Predictive Control (MPC)-based Trajectory Planners comprising a Longitudinal Trajectory Planner designed to compute a planned longitudinal trajectory for the automated motor-vehicle; and a Lateral Trajectory Planner designed to compute a planned lateral trajectory for the automated motor-vehicle. The electronic dynamics control system is further designed to cause the planned longitudinal trajectory to be computed before the planned lateral trajectory.

A control system (10) is suitable for use in one's own motor vehicle (12) and is configured and intended to use the environmental data provided to determine a position and a speed of a first motor vehicle (28) which is traveling directly ahead of one's own motor vehicle (12) in a first Lane (36), wherein one's own motor vehicle (12) is in the said lane (36). Furthermore, the control system is at least configured and intended to determine a position and a speed of a second motor vehicle (30) which is traveling in a lane (38) adjacent to the first lane (36) from the environmental data provided. Furthermore, the control system is configured and intended to detect from the environmental data provided whether there is a zipper situation. The control system is configured and intended to increase a target distance of one's own motor vehicle (12) to the first motor vehicle, if an amount of a relative speed of the second motor vehicle (30) relative to one's own motor vehicle (12) or relative to the first motor vehicle (28) is less than a predetermined first value, if the second motor vehicle (30) is located between one's own motor vehicle (12) and the first motor vehicle (28) in a longitudinal direction which extends along the adjacent lane (38), and if it was detected that the zipper situation applies.

The proposed invention relates to methods for controlling energy consumption by a motor vehicle, and can be used in transportation industry. The technical problem to be solved by the claimed invention is to provide a method and a non-transitory computer-readable medium that do not possess the drawbacks of the prior art and thus make it possible to generate an accurate energy-efficient track for a motor vehicle that allows to reduce energy consumption by the motor vehicle moving along a highway, including as part of a convoy.

The present disclosure provides a method and device for predicting a motion track of an obstacle and an autonomous vehicle, and relates to the technical field of autonomous driving, so as to at least solve the technical problem of low prediction precision of a motion track of an obstacle in an interaction scene. A specific implementation solution includes: environment information in a target scene, historical state information of a target obstacle and track planning information of a target vehicle are obtained, and the target obstacle is a potential interaction object of the target vehicle; and a motion track of the target obstacle is predicted based on the environment information, the historical state information and the track planning information.

Systems and methods for operating an autonomous vehicle (AV) are provided. The method includes detecting one or more objects in an environment, predicting a first set of predicted object trajectories comprising one or more trajectories for each of the detected one or more objects, generating a plurality of candidate AV trajectories for the AV, scoring each of the candidate AV trajectories according to a cost function, using the scoring to select a final AV trajectory for execution, determining which of the predicted object trajectories affected the final AV trajectory and which did not do so, adding the predicted object trajectories that affected the final AV trajectory to a persisted prediction cache, excluding from the persisted prediction cache any predicted object trajectories that did not affect the final AV trajectory, and executing the final AV trajectory to cause the AV to move along the final AV trajectory.