Study on Intelligent Vehicle Lane Change Path Planning and Control Simulation

摘要：

For autonomous Intelligent Vehicle (IV), lane change is an important lateral motion pattern which comprises path planning and path track control. Firstly, a kind of IV Lane Change Path Planning algorithm, which Satisfies Jerk Restraint (LCP2SJR), was developed. Then fuzzy-neural network (FNN) and genetic algorithm (GA) were used to design the IV Lane Change Robust Controller (LCRC). At last, simulations of the lane change track control were done. The results show that under the guidance of the path planed by LCP2SJR and the control of LCRC, IV can implements high precise, smooth and strong robust lane change motion.

关键词： intelligent vehicle lane change path planning robust control fuzzy-neural network genetic algorithm

作者: Jinxiang Feng Jiuhong Ruan Yibin Li

作者单位: ShanDong JiaoTong University Jinan, 250023, China Robot center ShanDong University Jinan, 250010, China

会议类型: 国际会议

会议名称: 2006 IEEE International Conference on Information Acquisition

会议地点: 山东威海

会议语种:英文

页码: 683-688

在线出版日期: 2006-08-20（万方平台首次上网日期，不代表论文的发表时间）