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Guidance Control for Parallel Parking Tasks

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  • 国家科技期刊平台
  • NETL
  • NSTL
  • 万方数据
  • 维普
Parking into small berths remains difficult for unskilled drivers.Researchers had proposed different automatic parking systems to solve this problem.The first kind of strategies (called parking trajectory planning) designs a detailed reference trajectory that links the start and ending points of a special parking task and let the vehicle track this reference trajectory so as to park into the berth.The second kind of strategies (called guidance control) just characterizes several regimes of driving actions as well as the important switching points in certain rule style and let the vehicle follows the pre-selected series of actions so as to park into the berth.Parking guidance control is simpler than parking trajectory planning.However,no studies thoroughly validated parking guidance control before.In this paper,a new automatic parking method is presented,which could characterize the desired control actions directly.Then the feasibility is examined carefully.Tests show that a simple parking guidance control strategy can work in most parallel parking tasks,if the available parking berth is not too small.This finding helps to build more concise automatic parking systems that can efficiently guide human drivers.

Automatic parkingguidance controltrajectory planning

Jiyuan Tan、Chunling Xu、Li Li、Fei-Yue Wang、Dongpu Cao、Lingxi Li

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Beijing Key Laboratory of Urban Intelligent Traffic Control Technology, North China University of Technology, Beijing 100144,China

Beijing Transport Institute, Beijing 100073, China

Department of Automation, BNRist, Tsinghua University,Beijing 100084, China

State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences,Beijing 100080, China

Cognition and Automated Driving Laboratory,University of Waterloo, Waterloo N2L 3G1, Canada

Department of Electrical and Computer Engineering,Purdue School of Engineering and Technology, Indiana University-Purdue University Indianapolis, Indiana 46202-5132 USA

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This work was supported in part by the National Key Research and Development Program of ChinaNational Natural Science Foundation of Chinaand the Joint Laboratory for Future Transport and Urban Computing of Amap

2018AAA010140061790565

2020

自动化学报(英文版)
中国自动化学会,中国科学院自动化研究所,中国科技出版传媒股份有限公司

自动化学报(英文版)

CSTPCDCSCDSCIEI
ISSN：2329-9266
年,卷(期)：2020.7(1)
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