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山东大学学报 (工学版) ›› 2021, Vol. 51 ›› Issue (6): 84-92.doi: 10.6040/j.issn.1672-3961.0.2021.353

• 土木工程 • 上一篇    

网联交通环境下的车-车通信故障诊断方法

闵海根1,2(),方煜坤1,*(),吴霞1,2,王武祺1   

  1. 1. 长安大学信息工程学院, 陕西 西安 710064
    2. “车联网”教育部-中国移动联合实验室, 陕西 西安 710021
  • 收稿日期:2021-07-05 出版日期:2021-12-20 发布日期:2022-01-19
  • 通讯作者: 方煜坤 E-mail:hgmin@chd.edu.cn;fangyukun@chd.edu.cn
  • 作者简介:闵海根(1990—), 男, 陕西安康人, 副教授, 博士, 主要研究方向为智慧交通, 智能网联汽车故障诊断及车路协同管控. E-mail: hgmin@chd.edu.cn
  • 基金资助:
    国家自然科学基金青年项目(61903046);陕西省重点研发计划(2021GY-290);陕西省高校科协青年人才托举计划项目(20200106);浙江省重点研发计划项目(2020C01057);中央高校基本科研业务费资助项目(300102240106)

Fault diagnosis of vehicle-to-vehicle communication in networked traffic environment

Haigen MIN1,2(),Yukun FANG1,*(),Xia WU1,2,Wuqi WANG1   

  1. 1. School of Information and Engineering, Chang′an University, Xi′an 710064, Shaanxi, China
    2. The Joint Laboratory for Internet of Vehicles, Ministry of Education-China Mobile Communications Corporation, Xi′an 710021, Shaanxi, China
  • Received:2021-07-05 Online:2021-12-20 Published:2022-01-19
  • Contact: Yukun FANG E-mail:hgmin@chd.edu.cn;fangyukun@chd.edu.cn

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摘要：

以智慧交通场景中的车辆编队为应用背景, 建立基于智能驾驶员模型的车辆队列控制模型, 分析车-车通信中延时对队列控制稳定性的影响。提出基于车-车通信更新延迟的故障诊断方法, 利用中值和均值的统计特性计算用于判断是否发生故障的决策变量, 设计两层滑窗对决策变量进行平滑, 实现决策变量实时、自适应计算; 利用Jarque-Bera检验一段时间内接收端延迟更新统计分布的正态性, 若该分布显著偏离正态分布, 则认为通信质量恶化。在测试场地采集车辆行驶速度数据和车-车通信延时数据, 对不同场景下车-车通信更新延迟的统计分布特性进行仿真试验, 验证车-车通信中延时对智能网联汽车协同控制的影响。研究结果表明, 车-车通信延时会导致协同控制过程中控制率的剧烈变化, 基于更新延迟的通信故障诊断方法可以对车-车通信质量是否恶化进行有效诊断。

关键词: 智慧交通, 智能网联汽车, 更新延迟, 自适应阈值, 车-车通信延时统计分布, 车-车通信故障诊断

Abstract:

With vehicle platoon in intelligent transportation system as the background, this research established a vehicle platoon control model based on the intelligent driver model and analyzed the influence of delay in vehicle-to-vehicle communication on the stability of platoon control. A fault diagnosis method based on the update delay of vehicle-to-vehicle communication was proposed. The statistical characteristics of median and average were used to calculate the decision variables which were used to judge whether a fault had occurred. A two-layer sliding window was designed to smooth the decision variables and adaptively calculate the decision variable in real time. The Jarque-Bera algorithm was used to test the normality of the statistical distribution of the receiver's update delay within a period of time. If the distribution significantly deviated from the normal distribution, it was considered that the communication quality had deteriorated. Collecting vehicle speed data and vehicle-to-vehicle communication delay data at the testbed, simulations were conducted to analyze the statistical distribution characteristics of the vehicle-vehicle communication update delay in different scenarios and verify the influence on vehicle platoon control of vehicle-to-vehicle communication delay. The research results showed that the vehicle-to-vehicle communication delay caused drastic changes in the control rate during the collaborative control process. The communication fault diagnosis method based on the update delay could effectively diagnose whether the vehicle-to-vehicle communication quality had deteriorated.

Key words: intelligent transportation, connected and automated vehicles, update delay, adaptive threshold, statistical distribution of vehicle-to-vehicle communication, fault diagnosis of vehicle-to-vehicle communication

中图分类号: 

  • U495

图1

测试平台及测试场地示意图"

表1

IDM模型数值仿真参数设置"

车辆数N/辆 期望行驶速度v0/(m·s-1) 期望的最小安全距离S0/m 期望车头时距Th/s 车身长度l/m 指数项δ 最大车辆加速度α/(m·s-2) 制动减速度β/(m·s-2)
6 10 10 1.2 2.5 4 2 1.5

图2

无V2V通信故障情况下IDM模型中各车辆速度和控制率随时间的变化"

图3

有V2V通信故障情况下IDM模型中各车辆速度和控制率随时间的变化"

图4

决策变量计算及故障点判决"

图5

静态环境下空旷和树木遮蔽场景不同距离情况下更新延迟的分布拟合"

图6

动态场景下不同速度情况下更新延迟的分布拟合"

1 LI Li , WEN Ding , YAO Danya . A survey of traffic control with vehicular communications[J]. IEEE Transactions on Intelligent Transportation Systems, 2014, 15 (1): 425- 432.
doi: 10.1109/TITS.2013.2277737
2 宋家成. 自主车辆队列分布式自适应控制研究[D]. 西安: 长安大学控制科学与工程系, 2018.
SONG Jiacheng. Study on distributed adaptive control of vehicle platoon[D]. Xi'an: Department of Control Science and Engineering, Chang'an University, 2018.
3 李科志. 车联网环境下基于反馈的智能车辆编队控制研究[D]. 重庆: 重庆邮电大学控制科学与工程系, 2017.
LI Kezhi. Feedback-based formation control for autonomous vehicles under connected environment[D]. Chongqing: Department of Control Science and Engineering, Chongqing University of Posts and Telecommunications, 2017.
4 ZHOU Bo , LIAO Xiaofeng . Leader-following second-order consensus in multi-agent systems with sampled data via pinning control[J]. Nonlinear Dynamics, 2014, 78 (1): 555- 569.
doi: 10.1007/s11071-014-1460-8
5 GU Haiyan , ZHANG Jian , JIN Jing , et al. Stability analysis of lead-vehicle control model in cooperative adaptive cruise control platoon within heterogeneous traffic flow[J]. Journal of Southeast University (English Edition), 2018, 34 (3): 386- 393.
6 GONG Siyuan , DU Lili . Cooperative platoon control for a mixed traffic flow including human drive vehicles and connected and autonomous vehicles[J]. Transportation Research Part B: Methodological, 2018, 116, 25- 61.
doi: 10.1016/j.trb.2018.07.005
7 PERRAKI G , RONCOLI C , PAPAMICHAIL I , et al. Evaluation of a model predictive control framework for motorway traffic involving conventional and automated vehicles[J]. Transportation Research Part C: Emerging Technologies, 2018, 92 (7): 456- 471.
8 徐成. 部分车辆联网条件下多车协同避障算法研究[D]. 北京: 清华大学机械工程系, 2015.
XU Cheng. Coordinated collision avoidance in partial-connected driving environment[D]. Beijing: Department of Mechanical Engineering, Tsinghua University, 2015.
9 LIU Bingyi , JIA Dongyao , LU Kejie , et al. A joint control-communication design for reliable vehicle platooning in hybrid traffic[J]. IEEE Transactions on Vehicular Technology, 2017, 66 (10): 9394- 9409.
doi: 10.1109/TVT.2017.2702650
10 BISWAS S , TATCHIKOU R , DION F . Vehicle-to-vehicle wireless communication protocols for enhancing highway traffic safety[J]. IEEE Communications Magazine, 2006, 44 (1): 74- 82.
doi: 10.1109/MCOM.2006.1580935
11 HU Sangen , WEN Huiying , XU Lunhui , et al. Stability of platoon of adaptive cruise control vehicles with time delay[J]. Transportation Letters, 2019, 11 (9): 506- 515.
doi: 10.1080/19427867.2017.1407488
12 WANG Meng . Infrastructure assisted adaptive driving to stabilise heterogeneous vehicle strings[J]. Transportation Research Part C Emerging Technologies, 2018, 91, 276- 295.
doi: 10.1016/j.trc.2018.04.010
13 PROTZMANN R. V2X communication in heterogeneous networks[D]. Berlin: Department of Electronic and Information Engineering, Technische Universität Berlin, 2018.
14 WANG Ziran . Motion estimation of connected and automated vehicles under communication delay and packet loss of V2X communications[J]. SAE Technical Paper, 2021, 4, 1- 10.
15 SHUI Yishui , FANG Li , YU Junyi , et al. Vehicle-to-vehicle radio channel characteristics for congestion scenario in dense urban region at 5.9 GHz[J]. International Journal of Antennas and Propagation, 2018, 2018, 1- 14.
16 NI Yuanzhi, HE Jianping, CAI Lin, et al. Delay analysis and message delivery strategy in hybrid V2I/V2V networks[C]// Proceedings of GLOBECOM 2016-2016 IEEE Global Communications Conference. Washington, USA: IEEE, 2016: 1-6.
17 PAVLOVIT D , SEKULOVIC N , MILOVANOVIC G , et al. Statistics for ratios of Rayleigh, Rician, Nakagami-m, and Weibull distributed random variables[J]. Mathematical Problems in Engineering, 2013, 2013, 657- 675.
18 CAO Liu, YIN Hao, HU Jie, et al. Performance analysis and improvement on DSRC application for V2V communication[C]//2020 IEEE 92nd Vehicular Technology Conference. Victoria, Canada: IEEE, 2020: 1-6. .
19 VIVEK N, SRIKANTH S V, SAURABH P, et al. On field performance analysis of IEEE 802.11p and WAVE protocol stack for V2V & V2I communication[C]//Proceedings of International Conference on Information Communication and Embedded Systems (ICICES2014). Chennai, India: IEEE, 2014: 1-6.
20 付留杰. 多智能体系统的故障诊断与容错控制方法研究[D]. 长春: 长春工业大学控制科学与工程系, 2017.
FULiujie. Research on fault diagnosis and fault-tolerant control of multi-agent system[D]. Changchun: Department of Control Science and Engineering, Changchun University of Technology, 2017.
21 ZHOU Mofan , QU Xiaobo , JIN Sheng . On the impact of cooperative autonomous vehicles in improving freeway merging: a modified intelligent driver model-based approach[J]. IEEE Transactions on Intelligent Transportation Systems, 2017, 18 (6): 1422- 1428.
22 TORABI H , HEDESH N M , GRANE A . A test for normality based on the empirical distribution function[J]. Statistics and Operations Research Transactions, 2016, 40 (1): 55- 88.
23 BERA J . A test for normality of observations and regression residuals[J]. International Statistical Review, 1987, 55 (2): 163- 172.
doi: 10.2307/1403192
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