Performance Analysis of Velocity Perturbation Control in Mixed Platoons with Connected Autonomous and Human-Driven Vehicles

Duan, X., Zhao, Y., Xia, H., Zhou, J., Zhang, L. and Zhao, D. (2022) Performance Analysis of Velocity Perturbation Control in Mixed Platoons with Connected Autonomous and Human-Driven Vehicles. In: 5th IEEE International Conference on Unmanned Systems (IEEE ICUS 2022), Guangzhou, China, 14-16 Oct 2022, pp. 799-804. ISBN 9781665484565 (doi: 10.1109/ICUS55513.2022.9986735)

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Abstract

As the Internet of vehicles and autonomous driving are not widely popularized, it is of practical significance to investigate the mixed platoon composed of connected autonomous and human-driven vehicles. This paper focuses on the velocity perturbation control of the mixed platoon. We first use an intelligent driver model (IDM) to build a general scene of an individual connected autonomous vehicle (CAV) guiding multiple human-driven vehicles (HDVs). Using this model, the paper theoretically derives the difficulty calculation of CAV controlling the velocity perturbation at a certain position in the whole platoon. The results show the relationship between the control difficulty and the control time of velocity perturbation occurring at different positions. Finally, the numerical simulation results verify that CAV has the potential to guide the HDVs behind it and eliminate the velocity perturbation. Interestingly, when the velocity perturbation occurs in a HDV far away from the CAV, the velocity perturbation will continue to exist for a long time.

Item Type:Conference Proceedings
Additional Information:This research was supported in part by the National Natural Science Foundation of China under Grant No. 62173012, U20A20155, and 51878019, in part by the Beijing Municipal Natural Science Foundation under Grant No. L191001, in part by the Beijing Municipal Key Research and Development Program under Grant No. Z211100001921004, in part by the Newton Advanced Fellowship under Grant No. 62061130221.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Zhao, Dr Dezong
Authors: Duan, X., Zhao, Y., Xia, H., Zhou, J., Zhang, L., and Zhao, D.
College/School:College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
ISSN:2771-7372
ISBN:9781665484565
Copyright Holders:Copyright © 2022 IEEE
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher
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