Intelligent bus route planning method based on multi-objective dynamic particle swarm optimization

Abstract

The invention discloses an intelligent bus vehicle path planning method based on multi-objective dynamic particle swarm optimization, which includes: obtaining vehicle and road information in real time, generating a global reference path; building a two-dimensional environment model based on road rule lines and the global reference path, and Initialize each particle in the particle swarm: each dimension of the particle corresponds to a coordinate point, and a curve segment is set between each two adjacent coordinate points to obtain the trajectory corresponding to the particle; according to the path length, smoothness and static safety indicators Design the static multi-objective fitness function of the trajectory; then use the particle swarm algorithm and apply the static multi-objective fitness function to extract the optimal trajectory candidate set; design the dynamic multi-objective fitness function and constraint acceleration relationship based on the dynamic obstacles, and combine them with The static safety design fitness function is combined to select a trajectory with the best comprehensive fitness from the optimal trajectory candidate set. The invention not only improves the comfort index, but also greatly improves the dynamic safety performance.

Description

technical field [0001] The invention relates to the technical field of intelligent driving and its control, in particular to an intelligent bus path planning method based on multi-objective dynamic particle swarm optimization. Background technique [0002] In recent years, intelligent driving has always been the focus of social attention. With the continuous advancement of intelligent driving technology research, intelligent vehicles have gradually come into reality. The structured urban roads and clear road signs also make the road conditions of urban buses relatively simple. These have prompted the bus to become a breakthrough in the popularization of automatic driving technology in daily life. The core part of automatic driving technology is to plan a safe and collision-free optimal driving path for intelligent vehicles. [0003] The research of path planning method is mainly to enable intelligent vehicles to avoid obstacles. Existing path planning algorithms can be divi...

AI Technical Summary

Problems solved by technology

However, there is a lack of a trajectory planning method for intelligent public vehicles that comprehensively considers static and dynamic multi-obstacle targets and ride comfort in the prior art.

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