Simulation and field testing of multiple vehicles collision avoidance algorithms

doi:10.1109/JAS.2020.1003246

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 平行智能技术与系统团队

	Simulation and field testing of multiple vehicles collision avoidance algorithms
	Zu, Chaoyue 1; Yang, Chao2 ; Wang, Jian 3,4; Gao, Wenbin 5; Cao, Dongpu 6; Wang, Fei-Yue7
发表期刊	IEEE-CAA JOURNAL OF AUTOMATICA SINICA
ISSN	2329-9266
	2020-07-01
卷号	7 期号:4 页码:1045-1063
通讯作者	Wang, Jian(wangjian591@jlu.edu.cn)
摘要	A global planning algorithm for intelligent vehicles is designed based on the A* algorithm, which provides intelligent vehicles with a global path towards their destinations. A distributed real-time multiple vehicle collision avoidance (MVCA) algorithm is proposed by extending the reciprocal n-body collision avoidance method. MVCA enables the intelligent vehicles to choose their destinations and control inputs independently, without needing to negotiate with each other or with the coordinator. Compared to the centralized trajectory-planning algorithm, MVCA reduces computation costs and greatly improves the robustness of the system. Because the destination of each intelligent vehicle can be regarded as private, which can be protected by MVCA, at the same time MVCA can provide a real-time trajectory planning for intelligent vehicles. Therefore, MVCA can better improve the safety of intelligent vehicles. The simulation was conducted in MATLAB, including crossroads scene simulation and circular exchange position simulation. The results show that MVCA behaves safely and reliably. The effects of latency and packet loss on MVCA are also statistically investigated through theoretically formulating broadcasting process based on one-dimensional Markov chain. The results uncover that the tolerant delay should not exceed the half of deciding cycle of trajectory planning, and shortening the sending interval could alleviate the negative effects caused by the packet loss to an extent. The cases of short delay (< 100 ms) and low packet loss (< 5%) can bring little influence to those trajectory planning algorithms that only depend on V2V to sense the context, but the unpredictable collision may occur if the delay and packet loss are further worsened. The MVCA was also tested by a real intelligent vehicle, the test results prove the operability of MVCA.
关键词	Collision avoidance intelligent vehicles inter-vehicle communication simulation testing trajectory planning
DOI	10.1109/JAS.2020.1003246
关键词[WOS]	TRAJECTORY GENERATION ; POTENTIAL FUNCTIONS
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61572229] ; National Natural Science Foundation of China[6171101066] ; Key Scientific and Technological Projects for Jilin Province Development Plan[20170204074GX] ; Key Scientific and Technological Projects for Jilin Province Development Plan[20180201068GX] ; Jilin Provincial International Cooperation Foundation[20180414015GH]
项目资助者	National Natural Science Foundation of China ; Key Scientific and Technological Projects for Jilin Province Development Plan ; Jilin Provincial International Cooperation Foundation
WOS研究方向	Automation & Control Systems
WOS类目	Automation & Control Systems
WOS记录号	WOS:000545416200012
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：34[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/40084
专题	多模态人工智能系统全国重点实验室_平行智能技术与系统团队
通讯作者	Wang, Jian
作者单位	1.Jilin Univ, Coll Comp Sci & Technol, Changchun 130012, Peoples R China 2.Jiangsu XCMG Construct Machinery Res Inst Ltd, Xuzhou 221004, Jiangsu, Peoples R China 3.Jilin Univ, Minist Educ, Coll Comp Sci & Technol, Key Lab Symbol Computat & Knowledge Engn, Changchun 130012, Peoples R China 4.Chongqing Xibu Automobile Proving Ground Manageme, Chongqing 404100, Peoples R China 5.State Grid JIBEI Elect Power Co Ltd, Management Training Ctr, Beijing, Peoples R China 6.Cranfield Univ, Adv Vehicle Engn Ctr, Cranfield MK43 0AL, Beds, England 7.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Zu, Chaoyue,Yang, Chao,Wang, Jian,et al. Simulation and field testing of multiple vehicles collision avoidance algorithms[J]. IEEE-CAA JOURNAL OF AUTOMATICA SINICA,2020,7(4):1045-1063.
APA	Zu, Chaoyue,Yang, Chao,Wang, Jian,Gao, Wenbin,Cao, Dongpu,&Wang, Fei-Yue.(2020).Simulation and field testing of multiple vehicles collision avoidance algorithms.IEEE-CAA JOURNAL OF AUTOMATICA SINICA,7(4),1045-1063.
MLA	Zu, Chaoyue,et al."Simulation and field testing of multiple vehicles collision avoidance algorithms".IEEE-CAA JOURNAL OF AUTOMATICA SINICA 7.4(2020):1045-1063.