Event-triggered vehicle-following control for connected and automated vehicles under nonideal vehicle-to-vehicle communications

Jizheng Liu; Zhenpo Wang; Lei Zhang

doi:10.1109/IV48863.2021.9575727

Event-triggered vehicle-following control for connected and automated vehicles under nonideal vehicle-to-vehicle communications

Jizheng Liu, Zhenpo Wang, Lei Zhang^*

^*Corresponding author for this work

School of Mechanical Engineering

Beijing Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

13 Citations (Scopus)

Abstract

In this paper, an event-triggered vehicle-following control scheme for connected and automated vehicles (CAVs) is proposed considering nonideal Vehicle-to- Vehicle communications such as communication delays and packet dropouts. An output-based event-triggered mechanism is employed for reducing computational burden. An Event-Triggered Model Predictive Control (ETMPC) is proposed by combining with a multi-target controller for the lateral and longitudinal vehicle-following control of CAVs. The simulation results demonstrate that the proposed ETMPC can avoid unnecessary optimization implementation, achieving a computational reduction by 61.5% while maintaining the tracking precision compared with a conventional Model Predictive Controller. The proposed control scheme is also capable of being employed in vehicle platoon control.

Original language	English
Title of host publication	32nd IEEE Intelligent Vehicles Symposium, IV 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	342-347
Number of pages	6
ISBN (Electronic)	9781728153940
DOIs	https://doi.org/10.1109/IV48863.2021.9575727
Publication status	Published - 11 Jul 2021
Event	32nd IEEE Intelligent Vehicles Symposium, IV 2021 - Nagoya, Japan Duration: 11 Jul 2021 → 17 Jul 2021

Publication series

Name	IEEE Intelligent Vehicles Symposium, Proceedings
Volume	2021-July

Conference

Conference	32nd IEEE Intelligent Vehicles Symposium, IV 2021
Country/Territory	Japan
City	Nagoya
Period	11/07/21 → 17/07/21

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10.1109/IV48863.2021.9575727

Cite this

Liu, J., Wang, Z., & Zhang, L. (2021). Event-triggered vehicle-following control for connected and automated vehicles under nonideal vehicle-to-vehicle communications. In 32nd IEEE Intelligent Vehicles Symposium, IV 2021 (pp. 342-347). (IEEE Intelligent Vehicles Symposium, Proceedings; Vol. 2021-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IV48863.2021.9575727

@inproceedings{ffb955074e074a8eb270acefbdf8afe9,

title = "Event-triggered vehicle-following control for connected and automated vehicles under nonideal vehicle-to-vehicle communications",

abstract = "In this paper, an event-triggered vehicle-following control scheme for connected and automated vehicles (CAVs) is proposed considering nonideal Vehicle-to- Vehicle communications such as communication delays and packet dropouts. An output-based event-triggered mechanism is employed for reducing computational burden. An Event-Triggered Model Predictive Control (ETMPC) is proposed by combining with a multi-target controller for the lateral and longitudinal vehicle-following control of CAVs. The simulation results demonstrate that the proposed ETMPC can avoid unnecessary optimization implementation, achieving a computational reduction by 61.5% while maintaining the tracking precision compared with a conventional Model Predictive Controller. The proposed control scheme is also capable of being employed in vehicle platoon control.",

author = "Jizheng Liu and Zhenpo Wang and Lei Zhang",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 32nd IEEE Intelligent Vehicles Symposium, IV 2021 ; Conference date: 11-07-2021 Through 17-07-2021",

year = "2021",

month = jul,

day = "11",

doi = "10.1109/IV48863.2021.9575727",

language = "English",

series = "IEEE Intelligent Vehicles Symposium, Proceedings",

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Liu, J, Wang, Z & Zhang, L 2021, Event-triggered vehicle-following control for connected and automated vehicles under nonideal vehicle-to-vehicle communications. in 32nd IEEE Intelligent Vehicles Symposium, IV 2021. IEEE Intelligent Vehicles Symposium, Proceedings, vol. 2021-July, Institute of Electrical and Electronics Engineers Inc., pp. 342-347, 32nd IEEE Intelligent Vehicles Symposium, IV 2021, Nagoya, Japan, 11/07/21. https://doi.org/10.1109/IV48863.2021.9575727

Event-triggered vehicle-following control for connected and automated vehicles under nonideal vehicle-to-vehicle communications. / Liu, Jizheng; Wang, Zhenpo ; Zhang, Lei.
32nd IEEE Intelligent Vehicles Symposium, IV 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 342-347 (IEEE Intelligent Vehicles Symposium, Proceedings; Vol. 2021-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - In this paper, an event-triggered vehicle-following control scheme for connected and automated vehicles (CAVs) is proposed considering nonideal Vehicle-to- Vehicle communications such as communication delays and packet dropouts. An output-based event-triggered mechanism is employed for reducing computational burden. An Event-Triggered Model Predictive Control (ETMPC) is proposed by combining with a multi-target controller for the lateral and longitudinal vehicle-following control of CAVs. The simulation results demonstrate that the proposed ETMPC can avoid unnecessary optimization implementation, achieving a computational reduction by 61.5% while maintaining the tracking precision compared with a conventional Model Predictive Controller. The proposed control scheme is also capable of being employed in vehicle platoon control.

AB - In this paper, an event-triggered vehicle-following control scheme for connected and automated vehicles (CAVs) is proposed considering nonideal Vehicle-to- Vehicle communications such as communication delays and packet dropouts. An output-based event-triggered mechanism is employed for reducing computational burden. An Event-Triggered Model Predictive Control (ETMPC) is proposed by combining with a multi-target controller for the lateral and longitudinal vehicle-following control of CAVs. The simulation results demonstrate that the proposed ETMPC can avoid unnecessary optimization implementation, achieving a computational reduction by 61.5% while maintaining the tracking precision compared with a conventional Model Predictive Controller. The proposed control scheme is also capable of being employed in vehicle platoon control.

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Event-triggered vehicle-following control for connected and automated vehicles under nonideal vehicle-to-vehicle communications

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