An improved sliding mode control (SMC) approach for enhancement of communication delay in vehicle platoon system

Li, Handong, Wu, Haimeng, Gulati, Ishita, Ali, Saleh A., Pickert, Volker and Dlay, Satnam S. (2022) An improved sliding mode control (SMC) approach for enhancement of communication delay in vehicle platoon system. IET Intelligent Transport Systems, 16 (7). pp. 958-970. ISSN 1751-956X

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Official URL: https://doi.org/10.1049/itr2.12189

Abstract

Vehicle platoon systems are widely recognized as a key enabler to address mass-transport. Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) are two technologies that drive platooning. The inter-vehicle spacing and the collaboration velocity in the platoon are main important parameters that must be controlled. Recently, a new mass-transport system has been proposed, called the Tracked Electric Vehicles (TEV). In TEV, the inter-vehicular spacing is reduced to only a quarter of the regular car length and cars drive at 200km/h which enable mass transport at uniform speed. However, conventional radar based Adaptive Cruise Control (ACC) system fail to control each vehicle in these scenarios. Lately, Sliding Mode Control (SMC) has been applied to control platoons with communication technology but with low speed and without delay. This paper proposes a novel SMC design for TEV using global dynamic information with the communication delay. Also, graph theory has been employed to investigate different V2V communication topology structures. To address the issues of node vehicle stability and string stability, Lyapunov candidate function is chosen and developed for in-depth analysis. In addition, this paper, uses first-order vehicle models with different acceleration and deceleration parameters for simulation validations under communication delay. The results show that this novel SMC has a significant tolerance ability therefore meet the design requirements of TEV.

Item Type: Article
Additional Information: Funding information: The research presented in this paper is supported by the Tracked Electric Vehicle(TEV) Project, Philadelphia Scientific UK) Limited.
Subjects: G400 Computer Science
G500 Information Systems
Department: Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering
Depositing User: John Coen
Date Deposited: 06 Apr 2022 10:07
Last Modified: 06 Jun 2022 13:45
URI: http://nrl.northumbria.ac.uk/id/eprint/48828

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