Vehicle lane change control method and device

Abstract

The embodiment of the invention discloses a vehicle lane change control method and device. The method includes: when the current vehicle needs path change, obtain the speed, position, acceleration and current road image of the current vehicle; based on the target detection model, detect the current other vehicle corresponding to the current vehicle from the current road image, and determine each The orientation information of the current other vehicle relative to the current vehicle; for each 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, determine the current other vehicle position; according to the speed, position, acceleration of the current vehicle and the current speed, position, and acceleration of other vehicles, if the path-based transformation model is obtained, the generated target satisfies the vehicle position constraint and makes the preset objective function reach the preset convergence condition The driving path performs path transformation operations according to the target driving path to improve the accuracy and efficiency of path planning.

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 ...

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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

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