Journal of South China University of Technology (Natural Science Edition) ›› 2021, Vol. 49 ›› Issue (5): 1-8.doi: 10.12141/j.issn.1000-565X.200371

Special Issue: 2021年交通运输工程

• Traffic & Transportation Engineering • Previous Articles     Next Articles

Construction of Autonomous Vehicles Test Scenarios with Typical Dangerous Accident Characteristics

CHEN Jiqing1,2 SHU Xiaoxiong1,2 LAN Fengchong1,2 WANG Junfeng1,2   

  1. 1.School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou 510640, Guangdong, China; 
    2.Guangdong Provincial Key Laboratory of Vehicle Engineering, Guangzhou 510640, Guangdong, China
  • Received:2020-06-29 Revised:2020-11-15 Online:2021-05-25 Published:2021-04-30
  • Contact: 兰凤崇（1959-），男，教授，博士生导师，主要从事车身结构与安全理论及相关技术研究。 E-mail:fclan@scut.edu.cn
  • About author:陈吉清（1966-)，女，教授，博士生导师，主要从事现代汽车设计方法研究。E-mail：chjq@scut.edu.cn
  • Supported by:
    Supported by the National Natural Science Foundation of China(51775193)and the National Automobile Accident In-Depth Investigation System Funding Project（ZL-ZHGT-2020014)

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Abstract: To meet the need of mass testing scenarios and high-risk scenarios for the autonomous vehicles safety testing and verification, and based on the accident data of 641 cases involving road section in the National Automobile Accident In-Depth Investigation System, five scene elements were selected according to traffic environment elements and test vehicle basic information elements. Then the vehicle accident data was analyzed by one-hot coding and cluster analysis methods. The dangerous accident characteristics were identified and analyzed by combining the vehicle accident data with the typical vehicle collision dangerous scenarios obtained by clustering. And 15 test scenarios of autonomous vehicles involving road section type were extracted, including 6 test scenarios involving common sections and 9 test scenarios involving intersections. Research shows that Chinese traffic environment has unique characteristics. In the test scenario, 53.3% of the target vehicles involved powered two-wheeler (including motorcycles and electric mopeds) and 40.0% involved M1 passenger vehicles. The proposed dangerous accident characteristics can better describe and clarify the test scenario.The research results can provide a test scenario with Chinese traffic environment characteristics for virtual testing of autonomous cars and a basis for the development and testing of vehicle active safety products.

Key words: vehicle traffic accident, test scenarios, clustering analysis, autonomous vehicles, dangerous accident characteristics

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