Safe and robust data-driven cooperative control policy for mixed vehicle platoons

Lan, J. , Zhao, D. and Tian, D. (2023) Safe and robust data-driven cooperative control policy for mixed vehicle platoons. International Journal of Robust and Nonlinear Control, 33(7), pp. 4171-4190. (doi: 10.1002/rnc.6412)

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This article considers mixed platoons consisting of both human-driven vehicles (HVs) and automated vehicles (AVs). The uncertainties and randomness in human driving behaviors highly affect the platoon safety and stability. However, most existing control strategies are either for platoons of pure AVs, or for special formations of mixed platoons with known HV models. This article addresses the control of mixed platoons with more general formations and unknown HV models. An innovative data-driven policy learning strategy is proposed to design the controllers for AVs based on vehicle-to-vehicle (V2V) communications. The policy learning strategy is embedded with the constraints of control input, inter-vehicular distance error and V2V communication topology. The strategy establishes a safe and robustly stable mixed platoon using prescribed communication topologies. The design efficacy is verified through simulations of a mixed platoon with different communication topologies and leader velocity profiles.

Item Type:Articles
Additional Information:This research was supported by the UK Engineering and Physical Sciences Research Council, Grant/Award Number: EP/S001956/1; UK Royal Society, Grant/Award Number: NAF⧵R1⧵201213; National Natural Science Foundation of China, Grant/Award Number: 62061130221; Leverhulme Trust, Grant/Award Number: ECF-2021-517.
Glasgow Author(s) Enlighten ID:Zhao, Dr Dezong and Lan, Dr Jianglin
Authors: Lan, J., Zhao, D., and Tian, D.
College/School:College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
Journal Name:International Journal of Robust and Nonlinear Control
ISSN (Online):1099-1239
Published Online:21 October 2022
Copyright Holders:Copyright © 2022 The Authors
First Published:First published in International Journal of Robust and Nonlinear Control 33(7): 4171-4190
Publisher Policy:Reproduced under a Creative Commons License

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
170256Understanding microbial community through in situ environmental 'omic data synthesisUmer Zeeshan IjazNatural Environment Research Council (NERC)NE/L011956/1ENG - Infrastructure & Environment