A V2V Empowered Consensus Framework for Cooperative Autonomous Driving

Cao, J., Leng, S., Zhang, L. , Imran, M. and Chai, H. (2022) A V2V Empowered Consensus Framework for Cooperative Autonomous Driving. In: 2022 IEEE Global Communications Conference (GLOBECOM), Rio de Janeiro, Brazil, 04-08 Dec 2022, pp. 5729-5734. ISBN 9781665435406 (doi: 10.1109/GLOBECOM48099.2022.10000723)

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Abstract

Cooperative autonomous driving has emerged as an appealing paradigm to expand the perception range of vehicles and improve driving safety by sharing local sensing data and driving intentions. However, the constrained communication resource and unstable link quality seriously restrict the coordination and reliability of driving decisions. The distributed consensus mechanism is a potential approach to address the problem. This paper proposes a fast and efficient vehicular consensus framework to improve the coordination and reliability of driving decisions in delay-sensitive applications. We first design a Raft empowered two-hop consensus mechanism with dynamic negotiation. Moreover, we theoretically analyze the performance of the mechanism in terms of successful consensus ratio, latency, and link quality by leveraging Jensen's inequality and binomial distribution. In addition, an adaptive joint design algorithm for consensus process and communication is put forward to minimize the consensus delay while satisfying the requirements of vehicular resources and coordination degree. Simulation results demonstrate that our proposed scheme can improve the reliability of critical decisions by 15.4% compared with existing approaches.

Item Type:Conference Proceedings
Additional Information:This work was partly supported by National Key R&D Program of China (No.2018YFE0117500), National Natural Science Foundation of China (No. 62171104).
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Zhang, Professor Lei and Imran, Professor Muhammad and Leng, Professor Supeng
Authors: Cao, J., Leng, S., Zhang, L., Imran, M., and Chai, H.
College/School:College of Science and Engineering > School of Engineering
College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
ISBN:9781665435406
Published Online:11 January 2023
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