Path planning and tracking for vehicle parallel parking based on preview BP neural network PID controller

被引：0

作者：

Ji X. ^{[1
]}

Wang J. ^{[2
]}

Zhao Y. ^{[2
]}

Liu Y. ^{[1
]}

Zang L. ^{[2
]}

Li B. ^{[2
]}

机构：

[1] State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing

[2] College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing

来源：

Transactions of Tianjin University | 2015年 / 21卷 / 03期

基金：

中国国家自然科学基金;

关键词：

BP neural network; curve fitting; parallel parking; path planning; path tracking;

D O I：

10.1007/s12209-015-2485-x

中图分类号：

学科分类号：

摘要：

In order to diminish the impacts of external disturbance such as parking speed fluctuation and model uncertainty existing in steering kinematics, this paper presents a parallel path tracking method for vehicle based on preview back propagation (BP) neural network PID controller. The forward BP neural network can adjust the parameters of PID controller in real time. The preview time is optimized by considering path curvature, change in curvature and road boundaries. A fuzzy controller considering barriers and different road conditions is built to select the starting position. In addition, a kind of path planning technology satisfying the requirement of obstacle avoidance is introduced. In order to solve the problem of discontinuous curvature, cubic B spline curve is used for curve fitting. The simulation results and real vehicle tests validate the effectiveness of the proposed path planning and tracking methods. © 2015, Tianjin University and Springer-Verlag Berlin Heidelberg.

引用

页码：199 / 208

页数：9

共 13 条

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