Lane changing control method and device for vehicle

Abstract

The embodiment of the invention discloses a lane changing control method and device for a vehicle. The method comprises the following steps: when a current vehicle needs path change, obtaining the speed, position, acceleration and current road image of the current vehicle; based on a target detection model, detecting current other vehicles corresponding to the current vehicle from the current roadimage, and determining orientation information of each current other vehicle relative to the current vehicle; for each current other vehicle, determining the position of the current other vehicle based on the position of the current vehicle, the orientation information of the current other vehicle relative to the current vehicle and the distance between the current other vehicle and the current vehicle. According to the speed, the position and the acceleration of the current vehicle and the speed, the position and the acceleration of the current other vehicles, if a target driving path whichis generated based on a path transformation model, meets vehicle position constraints and enables a preset target function to reach a preset convergence condition is obtained, path transformation operation is executed according to the target driving path, and the accuracy and efficiency of path planning are improved.

Description

technical field [0001] The present invention relates to the field of automatic driving, in particular to a method and device for controlling lane change of a vehicle. Background technique [0002] Motion planning is to find a constraint-compliant path for an unmanned vehicle between a given location A and location B. This constraint can be no collision, shortest path, minimum mechanical work, etc. It is an important research field of robotics. [0003] For safe and efficient unmanned vehicle planning, the planning method based on optimization solution can provide an optimal strategy for unmanned vehicles. Most of the existing path planning algorithms are based on search to generate a series of feasible trajectories satisfying the dynamics, and then filter out more suitable motion paths through collision detection and fusion of some artificial trajectory features. [0004] The above method has a large computational complexity in the implementation process, and cannot list ...

AI Technical Summary

Problems solved by technology

[0004] The above method has a large computational complexity in the implementation process, and cannot list all feasible trajectories, and is not suitable for real-time application process

Images