|Table of Contents|

Vehicle-infrastructure cooperative credible interaction method based on traffic business characteristics understanding(PDF)

《交通运输工程学报》[ISSN:1671-1637/CN:61-1369/U]

Issue:
2022年04期
Page:
348-360
Research Field:
交通信息工程及控制
Publishing date:

Info

Title:
Vehicle-infrastructure cooperative credible interaction method based on traffic business characteristics understanding
Author(s):
SHANGGUAN Wei1; 2;  ZHA Yuan-yuan1;  FU Yao3;  ZHENG Si-fa4;  CHAI Lin-guo1
(1. School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China; 2. State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044,China; 3. China Mobile Research Institute, Beijing 100053, China; 4. School of Vehicle and Mobility,Tsinghua University, Beijing 100084, China)
Keywords:
vehicle-infrastructure cooperation;  credible interaction;  traffic business characteristic understanding;  behavior state deduction;  path perturbation factor quantification;  multi-resolution cognition
PACS:
U495
DOI:
10.19818/j.cnki.1671-1637.2022.04.027
Abstract:
For the credible information interaction in vehicle-infrastructure cooperative environments, the processes of vehicle-vehicle and vehicle-infrastructure cooperative information interaction and the interaction requirements of different modes were analyzed, and a vehicle-infrastructure cooperative credible interaction framework was designed. A model of vehicle behavior state deduction and one of path perturbation factor quantification were constructed. A credibility calculation method for the vehicle object and level evaluation rules were designed. The credible authentication of vehicle object behavior was thereby achieved. A quantification model for the message urgency was built by understanding the effective traffic business characteristics. The low-resolution filtering strategy was used to preliminarily filter the message, and the message content was deeply understood on the basis of the support vector machine(SVM), thereby obtaining a multi-resolution interactive content cognition method. The Veins with OMNeT++ and SUMO simulators was used to build a simulation test environment. Simulation tests were carried out in open roads and intersection scenarios with different penetration rates of connected and automated vehicles(CAVs). The proposed vehicle-infrastructure cooperative credible interaction method was tested and verified. Research results show that the credibility identification for the vehicle-infrastructure cooperative information interaction can be effectively improved by understanding the traffic business characteristics. The average cognitive accuracy for the beacon location message achieved by the proposed method is 90.91%. It is 8.68% higher than that of the credible interaction method based on the timeliness detection. In the credible interaction verification experiment on the safety efficiency message, as the proportion of malicious vehicles increases, the traditional vehicle-infrastructure cooperative credible interaction method based on the voting mechanism is gradually held invalid. In contrast, an average accuracy of 94.96% is achieved by the proposed method under the condition that the single authentication delay is less than 13 ms. It is 3.05% higher than that of the traditional method based on the back propagation(BP)neural network. Moreover, a higher accuracy rate and a lower false negative rate of the credible interaction detection results can be obtained with a higher CAV penetration rate. Therefore, the needs of vehicle-infrastructure cooperative credible interaction can be met by the proposed method. 7 tabs, 15 figs, 31 refs.

References:

[1] CHEN Wei, GUO Fang-zhou, WANG Fei-yue. A survey of traffic data visualization[J]. IEEE Transactions on Intelligent Transportation Systems, 2015, 16(6): 2970-2984.
[2] YAO De-zhong, YU Chen, YANG L T, et al. Using
crowdsourcing to provide QoS for mobile cloud computing[J]. IEEE Transactions on Cloud Computing, 2019, 7(2): 344-356.
[3] 马永杰,程时升,马芸婷,等.卷积神经网络及其在智能交通系统中的应用综述[J].交通运输工程学报,2021,21(4):48-71.
MA Yong-jie, CHENG Shi-sheng, MA Yun-ting, et al. Review of convolutional neural network and its application in intelligent transportation system[J]. Journal of Traffic and Transportation Engineering, 2021, 21(4): 48-71.(in Chinese)
[4] LI Wen-jia, SONG Hou-bing. ART: an attack-resistant trust management scheme for securing vehicular ad hoc networks[J]. IEEE Transactions on Intelligent Transportation Systems, 2016, 17(4): 960-969.
[5] LU Zhao-jun, QU Gang, LIU Zheng-lin. A survey on recent advances in vehicular network security, trust, and privacy[J]. IEEE Transactions on Intelligent Transportation Systems, 2019, 20(2): 760-776.
[6] 张 毅,姚丹亚,李 力,等.智能车路协同系统关键技术与应用[J].交通运输系统工程与信息,2021,21(5):40-51.
ZHANG Yi, YAO Dan-ya, LI Li, et al. Technologies and applications for intelligent vehicle-infrastructure cooperation systems[J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(5): 40-51.(in Chinese)
[7] DENG Ruo-qi, DI Bo-ya, SONG Ling-yang. Cooperative
collision avoidance for overtaking maneuvers in cellular V2X-based autonomous driving[J]. IEEE Transactions on Vehicular Technology, 2019, 68(5): 4434-4446.
[8] 赵祥模,惠 飞,史 昕,等.泛在交通信息服务系统的概念、架构与关键技术[J].交通运输工程学报,2014,14(4):105-115.
ZHAO Xiang-mo, HUI Fei, SHI Xin, et al. Concept, architecture and challenging technologies of ubiquitous traffic information service system[J]. Journal of Traffic and Transportation Engineering, 2014, 14(4): 105-115.(in Chinese)
[9] CHETLUR V V, DHILLON H S. Coverage and rate analysis of downlink cellular vehicle-to-everything(C-V2X)communication[J]. IEEE Transactions on Wireless Communications, 2020, 19(3): 1738-1753.
[10] ALNASSER A, SUN Hong-jian, JIANG Jing. Cyber security challenges and solutions for V2X communications: a survey[J]. Computer Networks, 2019, 151: 52-67.
[11] AL-SULTAN S, Al-DOORI M M, AL-BAYATTI A H, et al. A comprehensive survey on vehicular ad hoc network[J]. Journal of Network and Computer Applications, 2014, 37: 380-392.
[12] 上官伟,史 斌,蔡伯根,等.车路协同环境下信道接入协议的优化方法[J].交通运输系统工程与信息,2016,16(6):47-53.
SHANGGUAN Wei, SHI Bin, CAI Bai-gen, et al. Optimization of channel access protocols and performance evaluation in cooperative vehicle infrastructure environment[J]. Journal of Transportation Systems Engineering and Information Technology, 2016, 16(6): 47-53.(in Chinese)
[13] GHOSAL A, CONTI M. Security issues and challenges in V2X: a survey[J]. Computer Networks, 2020, 169: 107093.
[14] 蔡伯根,王丛丛,上官伟,等.车路协同系统信息交互仿真方法[J].交通运输工程学报,2014,14(3):111-119.
CAI Bai-gen, WANG Cong-cong, SHANGGUAN Wei, et al. Simulation method of information interaction in CVIS[J]. Journal of Traffic and Transportation Engineering, 2014, 14(3): 111-119.(in Chinese)
[15] LI Teng-long, HUI Fei, ZHAO Xiang-mo, et al. Modelling heterogeneous traffic dynamics by considering the influence of V2V safety messages[J]. IET Intelligent Transport Systems, 2020, 14(4): 220-227.
[16] RAWAT D B, POPESCU D C, YAN Gong-jun, et al.
Enhancing VANET performance by joint adaptation of transmission power and contention window size[J]. IEEE Transactions on Parallel and Distributed Systems, 2011, 22(9): 1528-1535.
[17] 刘云璐,蒲菊华,方维维,等.一种无线传感器网络MAC协议优化算法[J].计算机学报,2012,35(3):529-539.
LIU Yun-lu, PU Ju-hua, FANG Wei-wei, et al. A MAC layer optimization algorithm in wireless sensor networks[J]. Chinese Journal of Computers, 2012, 35(3): 529-539.(in Chinese)
[18] TAN Shuai-shuai, LI Xiao-ping, DONG Qing-kuai. Trust based routing mechanism for securing OSLR-based MANET[J]. Ad Hoc Networks, 2015, 30: 84-98.
[19] VIJAYAKUMAR P, AZEES M, KANNAN A, et al. Dual authentication and key management techniques for secure data transmission in vehicular ad hoc networks[J]. IEEE Transactions on Intelligent Transportation Systems, 2016, 17(4): 1015-1028.
[20] VIJAYAKUMAR P, AZEES M, CHANG V, et al.
Computationally efficient privacy preserving authentication and key distribution techniques for vehicular ad hoc networks[J]. Cluster Computing, 2017, 20(3): 2439-2450.
[21] AZEES M, VIJAYAKUMAR P, DEBOARH L J. EAAP: efficient anonymous authentication with conditional privacy-preserving scheme for vehicular ad hoc networks[J]. IEEE Transactions on Intelligent Transportation Systems, 2017, 18(9): 2467-2476.
[22] 季一木,陆毅成,刘尚东,等.HIBE-MPJ:一种基于HIBE的物联网环境下跨域通信机制研究[J].南京邮电大学学报(自然科学版),2020,40(4):1-10.
JI Yi-mu, LU Yi-cheng, LIU Shang-dong, et al. HIBE-MPJ: cross-domain communication mechanism based on HIBE in Internet of things environment[J]. Journal of Nanjing University of Posts and Telecommunications(Natural Science Edition), 2020, 40(4): 1-10.(in Chinese)
[23] 郑明辉,段洋洋,吕含笑.车联网中基于群签名的身份认证协议研究[J].工程科学与技术,2018,50(4):130-134.
ZHENG Ming-hui, DUAN Yang-yang, LYU Han-xiao. Research on identity authentication protocol group signature-based in Internet of vehicles[J]. Advanced Engineering Sciences, 2018, 50(4): 130-134.(in Chinese)
[24] 杨雪婷,李 重.车联网中基于车辆行为预测的身份认证方案[J].计算机工程,2021,47(1):129-138.
YANG Xue-ting, LI Zhong. Identity authentication scheme based on vehicle behavior prediction for IoV[J]. Computer Engineering, 2021, 47(1): 129-138.(in Chinese)
[25] VUKADINOVIC V, BAKOWSKI K, MARSCH P, et al.
3GPP C-V2X and IEEE 802.11p for vehicle-to-vehicle communications in highway platooning scenarios[J]. Ad Hoc Networks, 2018, 74: 17-29.
[26] SHAIKH R A, ALZAHRANI A S. Intrusion-aware trust
model for vehicular ad hoc networks[J]. Security and Communication Networks, 2014, 7(11): 1652-1669.
[27] ARSHAD M, ULLAH Z, AHMAD N, et al. A survey of local/cooperative-based malicious information detection techniques in VANETs[J]. EURASIP Journal on Wireless Communications and Networking, 2018, 2018: 62.
[28] KIM T H J, STUDER A, DUBEY R, et al. VANET alert endorsement using multi-source filters[C]∥ACM. Proceedings of the Seventh ACM International Workshop on Vehicular Internetworking. New York: ACM, 2010: 51-60.
[29] YAO Xuan-xia, ZHANG Xin-lei, NING Huan-sheng, et al. Using trust model to ensure reliable data acquisition in VANETs[J]. Ad Hoc Networks, 2017, 55: 107-118.
[30] 刘伎昭,董跃钧.基于空间推理的车联网虚假消息检测方法[J].计算机工程与设计,2020,41(12):35-39.
LIU Ji-zhao, DONG Yue-jun. False messages detection method based on spatial inference in Internet of vehicles[J]. Computer Engineering and Design, 2020, 41(12): 35-39.(in Chinese)
[31] MUHAMMAD M, SAFDAR G A. Survey on existing
authentication issues for cellular-assisted V2X communication[J]. Vehicular Communications, 2018, 12: 50-65.

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Last Update: 2022-09-01