Journal of Jilin University(Engineering and Technology Edition) ›› 2025, Vol. 55 ›› Issue (2): 456-467.doi: 10.13229/j.cnki.jdxbgxb.20240874

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Continuous test scenario complexity evaluation method for automated driving vehicles

Bing ZHU1(),Tian-xin FAN1,Wen-bo ZHAO2,Wei-nan LI3,Pei-xing ZHANG1()   

  1. 1.National Key Laboratory of Automotive Chassis Integration and Bionics，Jilin University，Changchun 130022，China
    2.China Intelligent and Connected Vehicles （Beijing） Research Institute Co. ，Ltd. ，Beijing 100176，China
    3.China First Automobile Corporation R&D Center，Changchun 130011，China
  • Received:2024-08-05 Online:2025-02-01 Published:2025-04-16
  • Contact: Pei-xing ZHANG E-mail:zhubing@jlu.edu.cn;zhangpeixing@jlu.edu.cn

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Abstract:

Continuous test scenario is an important content of automated driving vehicle scenario-based testing system， but its fairness has been disputed. For this reason， this paper proposes a real-time evaluation method for the continuous test scenario complexity of automated driving vehicle， with a view to solving the problem of test scenario fairness. Based on the six-layer scenario model， a scenario element importance assessment system is established； through analyzing the mapping relationship between scenario elements and perception， decision-making， and execution systems， a quantitative evaluation method of scenario complexity at the system layer is constructed； the impact transfer weighting coefficients of different system are calculated， which can be used to realize the comprehensive calculation of scenario complexity in real time. The traffic circle continuous test scenario is selected to analyze the scenario complexity of two black-box automated driving systems， the results of the scenario complexity of the two vehicles are 1 and 0.765， which are consistent with the scenario complexity encountered by the two tested systems in the test process. The results can prove the effectiveness of the method proposed in this paper.

Key words: automotive engineering, automated driving vehicle, continuous test scenario, scenario complexity

CLC Number: 

  • U461

Fig.1

Scenario complexity evaluation framework"

Table 1

Scenario elements classification table"

一级分类二级分类三级分类

静态

场景

要素

道路层道路类型
道路质量
车道数量
道路标线
……
交通设施层信号灯
标志牌
其他设施
……
临时操作层交通事故
临时停放
道路施工
……

动态

场景

要素

目标层机动车
非机动车
行人
……
天气要素自然环境层光照
雨
雪
雾
……

Fig. 2

Point curve diagram of the relationship between point cloud and relative distance"

Table 2

Distribution table of influence coefficients of weather elements"

天气要素

传感器类型

传感器类型
相机毫米波雷达激光雷达
光照小10--
中0--
大5--
雨小402530
中704770
大755380
雪小20550
中403280
大606090
雾小101050
中252080
大604090

Fig. 3

Schematic diagram of the potential field of scenario elements"

Fig. 4

Map of reachable areas for automated driving vehicles"

Fig. 5

Schematic diagram of decision planning margins for automated driving vehicles"

Fig.6

Subsystem impact flowchart diagram for automated driving vehicles"

Fig.7

Continuous test scenario"

Table 3

Comprehensive Performance evaluation index table for automated driving vehicles"

总指标层权重指标层权重系统A系统B
安全性0.48避障平均车速118.1914.89
效率0.16平均变道时间15.448.72
智能性0.07避障平均最小TTC0.348.4012.56
车道保持距离道路中线最大距离0.660.720.63
舒适性0.29纵向加速度最大值0.622.572.10
横向加速度最大值0.382.061.53

Table 4

Scenario elements scoring table"

一级

分类

二级

分类

重要权重

系数

三级分类

重要权重

系数

属性特征评分
静态场景要素道路层0.1748道路类型0.356 53
道路质量0.113 61
车道数量0.265 02
道路标线0.265 01
交通设施层0.0828信号灯0.722 92
标志牌0.201 12
其他设施0.076 0-
临时操作层0.0667交通事故0.439 1-
临时停放0.318 7-
道路施工0.242 2-
动态场景要素目标层0.6757机动车0.128 83
非机动车0.260 94
行人0.610 33

Fig.8

Normalized decision planning margin diagram for automated driving vehicles"

Fig.9

Comparison chart of road segments of automated driving vehicles"

Table 5

Scenario elements-system complexity mapping relationship table"

复杂度系统A系统B
感知系统8.030 26.849 7
决策系统0.525 10.295 8
执行系统1.478 41.327 0

Table 6

Comprehensive performance evaluation table for automated driving vehicles"

评价项目系统A系统B
不考虑场景复杂度的评分0.840.94
场景相对复杂度10.765
考虑场景复杂度的评分0.840.72
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