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| Simulation and Field Testing of Multiple Vehicles Collision Avoidance Algorithms | |
Chaoyue Zu; Chao Yang ; Jian Wang; Wenbin Gao; Dongpu Cao; Fei-Yue Wang
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| Source Publication | IEEE/CAA Journal of Automatica Sinica
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| ISSN | 2329-9266 |
| 2020 | |
| Volume | 7Issue:4Pages:1045-1063 |
| Abstract | 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. |
| Keyword | Collision avoidance intelligent vehicles inter-vehicle communication simulation testing trajectory planning |
| DOI | 10.1109/JAS.2020.1003246 |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.ia.ac.cn/handle/173211/43026 |
| Collection | 学术期刊_IEEE/CAA Journal of Automatica Sinica |
| Recommended Citation GB/T 7714 | Chaoyue Zu,Chao Yang,Jian Wang,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 | Chaoyue Zu,Chao Yang,Jian Wang,Wenbin Gao,Dongpu Cao,&Fei-Yue Wang.(2020).Simulation and Field Testing of Multiple Vehicles Collision Avoidance Algorithms.IEEE/CAA Journal of Automatica Sinica,7(4),1045-1063. |
| MLA | Chaoyue Zu,et al."Simulation and Field Testing of Multiple Vehicles Collision Avoidance Algorithms".IEEE/CAA Journal of Automatica Sinica 7.4(2020):1045-1063. |
| Files in This Item: | Download All | |||||
| File Name/Size | DocType | Version | Access | License | ||
| JAS-2018-0129.pdf（40115KB） | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | View Download | |
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