基于多目标动态粒子群优化的智能公交车辆路径规划方法

• Format: Patent
• Language: Chinese
• Published: 30.10.2020
• Subjects: CONTROLLING; PHYSICS; REGULATING; SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES

本发明公开了一种基于多目标动态粒子群优化的智能公交车辆路径规划方法，包括：实时获取车辆和道路信息，生成全局参考路径；基于道路规则线和全局参考路径构建二维环境模型，并初始化粒子群中每个粒子：粒子的每个维度对应一个坐标点，每相邻两个维度坐标点之间设定曲线段，得到粒子对应的轨迹；根据路径长度、平滑度以及静态安全度指标设计轨迹的静态多目标适应度函数；然后采用粒子群算法，并应用静态多目标适应度函数，提取最优轨迹候选集；根据动态障碍物设计动态多目标适应度函数和约束加速度关系，并与静态安全性设计适应度函数结合，从最优轨迹候选集中选择综合适应度最优的一条轨迹。本发明在改善舒适性指标同时，大大提高动态安全性能。 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 accor