Nonlinear consensus-based autonomous vehicle platoon control under 
event-triggered strategy in the presence of time delays

Wang, Weiping; Wang, Chunyang; Wang, Zhen; Han, Baijing; He, Chang; Cheng, Jun; Luo, Xiong; Yuan, Manman; Kurths, Jürgen

doi:10.1016/j.amc.2021.126246

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Nonlinear consensus-based autonomous vehicle platoon control under event-triggered strategy in the presence of time delays

Wang, W., Wang, C., Wang, Z., Han, B., He, C., Cheng, J., Luo, X., Yuan, M., Kurths, J. (2021): Nonlinear consensus-based autonomous vehicle platoon control under event-triggered strategy in the presence of time delays. - Applied Mathematics and Computation, 404, 126246.
https://doi.org/10.1016/j.amc.2021.126246

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Item Permalink: https://publications.pik-potsdam.de/pubman/item/item_25806 Version Permalink: https://publications.pik-potsdam.de/pubman/item/item_25806_1

Genre: Journal Article

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Creators:
Wang, Weiping¹, Author
Wang, Chunyang¹, Author
Wang, Zhen¹, Author
Han, Baijing¹, Author
He, Chang¹, Author
Cheng, Jun¹, Author
Luo, Xiong¹, Author
Yuan, Manman¹, Author
Kurths, Jürgen², Author

Affiliations:
1External Organizations, ou_persistent22
2Potsdam Institute for Climate Impact Research, ou_persistent13

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Abstract: A novel platoon control algorithm for autonomous vehicles is proposed in this paper. There is an interaction between adjacent vehicles. In order to describe this interaction, a nonlinear function is designed. Then a non-linear distributed event-triggered controller with time delay is designed for the two cases of communication delay. In order to save resources furtherly, we have designed an event-triggered control strategy. In addition, the consensus of autonomous vehicles is guaranteed. Combining with Lyapunov’s theory, we derive the upper bound of time delay of vehicle platoon. Finally, we give two simulation examples to verify the feasibility and accuracy of the method.

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Dates: Published Online: 2021-03-26Finally published : 2021-04-13

Publication Status: Finally published

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Rev. Type: Peer

Identifiers: DOI: 10.1016/j.amc.2021.126246
MDB-ID: No data to archive
Research topic keyword: Complex Networks
Research topic keyword: Nonlinear Dynamics
Model / method: Machine Learning
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science

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Title: Applied Mathematics and Computation

Source Genre: Journal, SCI, Scopus

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Pages: - Volume / Issue: 404 Sequence Number: 126246 Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/applied-mathematics-computation
Publisher: Elsevier