Decentralized Model Predictive Control for Automated and Connected Electric Vehicles at Signal-free Intersections

Xiao Pan; Boli Chen; Li Dai; Stelios Timotheou; Simos A. Evangelou

doi:10.1109/CDC45484.2021.9683495

Decentralized Model Predictive Control for Automated and Connected Electric Vehicles at Signal-free Intersections

Xiao Pan
, Boli Chen
, Li Dai
, Stelios Timotheou
, Simos A. Evangelou

School of Automation

Imperial College London
University College London
University of Cyprus

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

4 Citations (Scopus)

Abstract

The development of connected and automated vehicles (CAVs) enables improvements in the safety, smoothness, and energy efficiency of the road transportation systems. This paper addresses the problem of optimally controlling battery-electric CAVs crossing an unsignalized intersection subject to a first-in-first-out crossing policy. The optimal velocity trajectory of each vehicle that minimizes the average energy consumption and travel time, is found by a decentralized model predictive control (DMPC) method via a convex modeling framework so as to ensure computational efficiency and the optimality of the solution. Numerical examples and comparisons with a centralized control counterpart demonstrate the effectiveness of the proposed decentralized coordination scheme and the trade-off between energy consumption and travel time. Further investigation into the size of the sampling interval is also provided in order to show the validity of the method in practice.

Original language	English
Title of host publication	60th IEEE Conference on Decision and Control, CDC 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2659-2664
Number of pages	6
ISBN (Electronic)	9781665436595
DOIs	https://doi.org/10.1109/CDC45484.2021.9683495
Publication status	Published - 2021
Event	60th IEEE Conference on Decision and Control, CDC 2021 - Austin, United States Duration: 13 Dec 2021 → 17 Dec 2021

Publication series

Name	Proceedings of the IEEE Conference on Decision and Control
Volume	2021-December
ISSN (Print)	0743-1546
ISSN (Electronic)	2576-2370

Conference

Conference	60th IEEE Conference on Decision and Control, CDC 2021
Country/Territory	United States
City	Austin
Period	13/12/21 → 17/12/21

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Access to Document

10.1109/CDC45484.2021.9683495

Cite this

Pan, X., Chen, B., Dai, L., Timotheou, S., & Evangelou, S. A. (2021). Decentralized Model Predictive Control for Automated and Connected Electric Vehicles at Signal-free Intersections. In 60th IEEE Conference on Decision and Control, CDC 2021 (pp. 2659-2664). (Proceedings of the IEEE Conference on Decision and Control; Vol. 2021-December). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CDC45484.2021.9683495

@inproceedings{31b14a1a35c34863b5b62a4eadf5d0d4,

title = "Decentralized Model Predictive Control for Automated and Connected Electric Vehicles at Signal-free Intersections",

abstract = "The development of connected and automated vehicles (CAVs) enables improvements in the safety, smoothness, and energy efficiency of the road transportation systems. This paper addresses the problem of optimally controlling battery-electric CAVs crossing an unsignalized intersection subject to a first-in-first-out crossing policy. The optimal velocity trajectory of each vehicle that minimizes the average energy consumption and travel time, is found by a decentralized model predictive control (DMPC) method via a convex modeling framework so as to ensure computational efficiency and the optimality of the solution. Numerical examples and comparisons with a centralized control counterpart demonstrate the effectiveness of the proposed decentralized coordination scheme and the trade-off between energy consumption and travel time. Further investigation into the size of the sampling interval is also provided in order to show the validity of the method in practice.",

author = "Xiao Pan and Boli Chen and Li Dai and Stelios Timotheou and Evangelou, \{Simos A.\}",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 60th IEEE Conference on Decision and Control, CDC 2021 ; Conference date: 13-12-2021 Through 17-12-2021",

year = "2021",

doi = "10.1109/CDC45484.2021.9683495",

language = "English",

series = "Proceedings of the IEEE Conference on Decision and Control",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Pan, X, Chen, B, Dai, L, Timotheou, S & Evangelou, SA 2021, Decentralized Model Predictive Control for Automated and Connected Electric Vehicles at Signal-free Intersections. in 60th IEEE Conference on Decision and Control, CDC 2021. Proceedings of the IEEE Conference on Decision and Control, vol. 2021-December, Institute of Electrical and Electronics Engineers Inc., pp. 2659-2664, 60th IEEE Conference on Decision and Control, CDC 2021, Austin, United States, 13/12/21. https://doi.org/10.1109/CDC45484.2021.9683495

Decentralized Model Predictive Control for Automated and Connected Electric Vehicles at Signal-free Intersections. / Pan, Xiao; Chen, Boli; Dai, Li et al.
60th IEEE Conference on Decision and Control, CDC 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 2659-2664 (Proceedings of the IEEE Conference on Decision and Control; Vol. 2021-December).

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

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AU - Pan, Xiao

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AU - Timotheou, Stelios

AU - Evangelou, Simos A.

PY - 2021

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N2 - The development of connected and automated vehicles (CAVs) enables improvements in the safety, smoothness, and energy efficiency of the road transportation systems. This paper addresses the problem of optimally controlling battery-electric CAVs crossing an unsignalized intersection subject to a first-in-first-out crossing policy. The optimal velocity trajectory of each vehicle that minimizes the average energy consumption and travel time, is found by a decentralized model predictive control (DMPC) method via a convex modeling framework so as to ensure computational efficiency and the optimality of the solution. Numerical examples and comparisons with a centralized control counterpart demonstrate the effectiveness of the proposed decentralized coordination scheme and the trade-off between energy consumption and travel time. Further investigation into the size of the sampling interval is also provided in order to show the validity of the method in practice.

AB - The development of connected and automated vehicles (CAVs) enables improvements in the safety, smoothness, and energy efficiency of the road transportation systems. This paper addresses the problem of optimally controlling battery-electric CAVs crossing an unsignalized intersection subject to a first-in-first-out crossing policy. The optimal velocity trajectory of each vehicle that minimizes the average energy consumption and travel time, is found by a decentralized model predictive control (DMPC) method via a convex modeling framework so as to ensure computational efficiency and the optimality of the solution. Numerical examples and comparisons with a centralized control counterpart demonstrate the effectiveness of the proposed decentralized coordination scheme and the trade-off between energy consumption and travel time. Further investigation into the size of the sampling interval is also provided in order to show the validity of the method in practice.

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M3 - Conference contribution

AN - SCOPUS:85126037464

T3 - Proceedings of the IEEE Conference on Decision and Control

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BT - 60th IEEE Conference on Decision and Control, CDC 2021

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ER -

Pan X, Chen B, Dai L, Timotheou S, Evangelou SA. Decentralized Model Predictive Control for Automated and Connected Electric Vehicles at Signal-free Intersections. In 60th IEEE Conference on Decision and Control, CDC 2021. Institute of Electrical and Electronics Engineers Inc. 2021. p. 2659-2664. (Proceedings of the IEEE Conference on Decision and Control). doi: 10.1109/CDC45484.2021.9683495

Decentralized Model Predictive Control for Automated and Connected Electric Vehicles at Signal-free Intersections

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