智能网联汽车协同感知信任度动态计算与评价方法

doi:10.19562/j.chinasae.qcgc.2023.08.009

Abstract

Abstract:

Collaborative perception technology enhances the perceptual performance of intelligent connected vehicles， but abnormal vehicles and malicious attack information in the collaborative network can affect the authenticity and effectiveness of collaborative perception results. To address this problem， an intelligent connected vehicle trustworthiness dynamic aggregation and evaluation method is proposed in this paper， based on occlusion state discrimination and detection effectiveness identification strategy， combined with detection results in the vehicle collaborative network. Simulation results show that the proposed collaborative perception trust evaluation method improves the reliability of detection results for collaborative perception vehicles， enhances the robustness of the intelligent connected vehicle collaborative perception process， and realizes dynamic identification of sudden malicious attacks of high-trust vehicles by the trust management model.

Key words: intelligent connected vehicle, cooperative perception, dynamic aggregation, trust evaluation

Bing Zhu,Hongyi Jiang,Jian Zhao,Jiayi Han,Yanchen Liu. A Method for Dynamically Calculating and Evaluating the Trustworthiness of Collaborative Perception of Intelligent Connected Vehicles[J].Automotive Engineering, 2023, 45(8): 1383-1391.

Figures/Tables 11

算法1：检测有效性判别

输入： 协同车辆集合 $V = v 1, v 2, …, v i j ≠ i$ ；

车辆检测对象集合 $D v 1, D v 2, …, D v j$ ；

集合 $V$ 中车辆对检测遮挡状态的集合 $Θ v j v i β n v j$

输出：车辆检测评价有效性集合 $E v a$

//车辆vi对集合中车辆vj的检测对象有效性进行识别

1. for $v j$ in $V$ do

2. for $β n v j, O v i β n v j$ in $Θ v j v i β n v j$

3. $O g l o b a l i j, n = O v i β n v j$

4. while $O g l o b a l i j, n ≠ 0$ do //遮挡状态为“可见”

5. if $β n v j ? D v j$ then //判断 $β n v j$ 是否在 $D v j$ 中

6. $Ω i j, n = - 1$ //不在，判定为非正常检测状态

7. else

8. $Ω i j, n = 1$ //在，判定为正常检测状态

9. end while

10. $n + +$

11. end for

12. $? j + +$

13. end for

14. //通过不同车辆视角下的检测状态，累计判定 $β n v j$ 的有效性

15. $? S t a t e j, n = z e r o s$

16. for $Ω i j, n$ in $Ω$ do //累计判别

17. $S t a t e j, n ? + = Ω i j, n$

18. $? i + +$

19. end for

20. for $v j$ in $V$ do

21. if $Ω i j, n ? S t a t e j, n ≥ 0$ //评价有效性判断

22. $E v a i j, n = 1$ //车辆 $v j$ 的 $β n v j$ 为有效检测对象

23. else

24. $E v a i j, n = 0$ //车辆 $v j$ 的 $β n v j$ 为无效检测对象

25. $j + +$

26. end for

References 23

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A Method for Dynamically Calculating and Evaluating the Trustworthiness of Collaborative Perception of Intelligent Connected Vehicles

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