|
|
|
| Evaluation Model of Intelligent Vehicle Test Condition Based on Risk Degree and Complexity Degree |
| LI Wen-liang1, ZHAN Qi1, ZHOU Wei1, SONG Yi2, ZHANG Jin-ling2 |
1. Key Laboratory of operation safety technology on transport vehicles, Ministry of Transport, PRC, Beijing 100088, China;
2. Beijing University of Posts and Telecommunications, Beijing 100876, China |
|
|
|
|
Abstract In order to study the quantitative evaluation of the effectiveness of intelligent vehicle under test conditions, the risk model based on driving risk field was improved, and the complexity degree of each elements of driving environment was defined. Considering risk degree and complexity degree coverage, maximum and distribution of user and test conditions, an evaluation model of user and test conditions based on risk degree and complexity degree was constructed. The validity of three tests was analyzed and evaluated by examples. The results showed that the effectiveness index could be used to evaluate the effectiveness of the test conditions quantitatively.
|
|
Received: 30 January 2021
|
| Fund:Supported by the National Key Research and Development Program (No. 2017YFC0804808) |
|
Corresponding Authors:
LI Wen-liang
E-mail: wl.li@rioh.cn
|
|
|
|
[1] China Society of Automotive Engineers. Technology Roadmap for Energy Saving and New Energy Vehicles[M]. Beijing:China Machine Press, 2016. (in Chinese)
[2] LUO Hong-mei, ZHOU Yi-fan. The Development of the Smart Car Industry[J]. Motorcycle Technology, 2019,29(3):54-57. (in Chinese)
[3] WANG Yu. Research on Auto Intelligentization Index and Appraising Methods[D].Changchun:Jilin University, 2018. (in Chinese)
[4] LI Xiao-qing, LIU Qi, LI Bing-lin, et al. Research on Selection and Classification of Intelligent Connected Vehicle Public Testing Roads[J].Journal of Transportation Engineering, 2019,19(5):74-78. (in Chinese)
[5] GUO Peng, RONG Hui, WANG Wen-yang, et al. Research on the Development Status of Intelligent Connected Vehicle Demonstration Zone Already Built in China[J]. Auto Electric Parts, 2018,57(5):15-19. (in Chinese)
[6] WU Hai-fei, SONG Xue-song, CAO Yin. Research on Test and Evaluation Method System of Autonomous Driving Vehicle[J]. Quality and Standardization, 2018,18(5):50-52. (in Chinese)
[7] SUN Jian, HUANG Run-han, LI Lin, et al. Integrated Simulation Test Platform for Environment Perception and Planning Decision of Intelligent Vehicle[J]. Journal of System Simulation,2020,32(2):1-11. (in Chinese)
[8] ZHANG Wei, LI Xin-hui, WU Xue-yi, et al. Research Status of Autonomous Vehicle Simulation Technology[J]. Auto Electric Parts,2019,60(8):13-15. (in Chinese)
[9] ZHAO Xiang-mo, CHENG Jing-jun, XU Zhi-gang, et al. An Indoor Rapid-testing Platform for Autonomous Vehicle Based on Vehicle-in-the-loop Simulation[J]. China Journal of Highway and Transport, 2019,32(6):124-136. (in Chinese)
[10] CHEN Tao, CAI Bo, HUI Chun. Research on Scene Construction of Intelligent Connected Vehicle Based on Scene Elements[J].Highways & Automotive Applications,2019,37(6):9-12. (in Chinese)
[11] JIANG Li-jun. Research on Test and Evaluation Method of Autonomous Emergency Breaking System[D]. Shanghai:Tongji University, 2014. (in Chinese)
[12] SU Jiang-ping, CHEN Jun-yi,WANG Hong-yan,et al. Establishment and Analysis on Typical Road Traffic Near-Crash Scenarios Related to Pedestrian in China[J]. Traffic & Transportation,2017,33(1):209-214. (in Chinese)
[13] LIU Ying,HE Jin-peng,LIU Wei-guo,et al. Research on Test Scenarios for AEB Pedestrian System[J]. Automobile Technology,2014,45(3):35-39. (in Chinese)
[14] LI Wen-liang, ZHOU Wei, ZHANG Lu, et al. A Method for Constructing Customer Target Load Spectrum Considering Distribution of Road Roughness and Velocity[J]. Journal of Highway and Transportation Research and Development, 2016, 33(12):154-158. (in Chinese)
[15] ZHOU Wei, LI Wen-liang, GUO Zhi-ping, et al. Study on Enhancement Coefficient of Washboard Road of Automobile Proving Ground[J]. Journal of Highway and Transportation Research and Development,2008, 25(11):140-144. (in Chinese)
[16] LI Wen-liang, ZHOU Wei, ZHANG Lu. A Method for Constructing Reliability Target Load Spectrum of Taxi Customer[J]. Journal of Highway and Transportation Research and Development,2016,33(2):130-134. (in Chinese)
[17] WANG Jian-qiang, WU Jian, LI Yang. Concept, Principle and Modeling of Driving Risk Field Based on Driver-vehicle-road Interaction[J]. China Journal of Highway and Transport,2016,29(1):105-114. (in Chinese)
[18] LI Wen-liang, ZHOU Wei, SONG Yi, et al. A Model for Evaluating Correlation between Test Condition and User Condition of Intelligent Vehicle[J].Journal of Highway and Transportation Research and Development, 2020,37(8):144-148. (in Chinese) |
|
|
|
2021, Vol. 15 
