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

Abstract

The invention discloses an intelligent public transport vehicle path planning method based on multi-objective dynamic particle swarm optimization. The method comprises the following steps: obtaining vehicle and road information in real time, and generating a global reference path; constructing a two-dimensional environment model based on the road rule line and the global reference path, and initializing each particle in the particle swarm: each dimension of the particle corresponds to one coordinate point, and setting a curve segment between coordinate points of every two adjacent dimensions to obtain a track corresponding to the particle; designing a static multi-objective fitness function of the trajectory according to the path length, the smoothness and the static safety index; secondly, extracting an optimal trajectory candidate set by adopting a particle swarm algorithm and applying a static multi-target fitness function; and designing a dynamic multi-target fitness function and aconstraint acceleration relationship according to the dynamic obstacle, combining the dynamic multi-target fitness function and the constraint acceleration relationship with a static safety design fitness function, and selecting a track with optimal comprehensive fitness from the optimal track candidate set. The dynamic safety performance is greatly improved while the comfort index is improved.

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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