文章基本信息

标题：Research on path planning based on new fusion algorithm for autonomous vehicle
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作者：ChaoChun Yuan ; Yue Wei ; Jie Shen 等
期刊名称：International Journal of Advanced Robotic Systems
印刷版ISSN：1729-8806
电子版ISSN：1729-8814
出版年度：2020
卷号：17
期号：3
页码：1-15
DOI：10.1177/1729881420911235
出版社：SAGE Publications
摘要：Ant colony algorithm or artificial potential field is commonly used for path planning of autonomous vehicle. However, vehicle dynamics and road adhesion coefficient are not taken into consideration. In addition, ant colony algorithm has blindness/randomness due to low pheromone concentration at initial stage of obstacle avoidance path searching progress. In this article, a new fusion algorithm combining ant colony algorithm and improved potential field is introduced making autonomous vehicle avoid obstacle and drive more safely. Controller of path planning is modeled and analyzed based on simulation of CarSim and Simulink. Simulation results show that fusion algorithm reduces blindness at initial stage of obstacle avoidance path searching progress and verifies validity and efficiency of path planning. Moreover, all parameters of vehicle are changed within a reasonable range to meet requirements of steering stability and driving safely during path planning progress..
关键词：Autonomous vehicle ; path planning ; fusion algorithm (improved ant colony algorithm (IACA) ; improved artificial potential field (IAPF)) ; road adhesion coefficient ; environment perception ; pheromone update