Definition and Quantification of the Complexity Experienced by Autonomous Vehicles in the Environment and Driving Task

被引:0
|
作者
Ma, Yining [1 ]
Pan, Xinfu [2 ]
Xiong, Lu [1 ]
Xing, Xingyu [3 ]
Bulut, Serdar [1 ]
Chen, Junyi [1 ]
机构
[1] Tongji Univ, Sch Automot Studies, Shanghai, Peoples R China
[2] CATARC Yancheng Automot Proving Ground Co Ltd, Yancheng, Jiangsu, Peoples R China
[3] Tech Univ Darmstadt, Dept Comp Integrated Design, Darmstadt, Germany
来源
CICTP 2020: TRANSPORTATION EVOLUTION IMPACTING FUTURE MOBILITY | 2020年
基金
国家重点研发计划;
关键词
Autonomous vehicles; Complexity of environment; Driving task; Uncertainty; Quantification methodology;
D O I
暂无
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Research on complexity of environment and driving task is critical in testing and validating L3+ autonomous vehicles (AVs). We define the complexity of environment and driving task of AVs as the sum of uncertainties in the prediction process and propose a method to quantify it. Based on the analysis of the effect factors of perception system and the data processing algorithm of the cognition system of AV, and combining with complexity theory and the definition mentioned above, several types of environmental complexity factors liked the amount, variety, and path of motion of objects, the environment conditions are abstracted. Multi-factor analysis quantification is used to generate a quantifying model for the complexity of environment. A survey among five experts in the field of autonomous driving is conducted. The consistency between the average survey results and the quantification by using this methodology is 81%, which proves the effectiveness of this methodology.
引用
收藏
页码:1030 / 1042
页数:13
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