UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Optimal Motion Control for Connected and Automated Electric Vehicles at Signal-Free Intersections

Pan, X; Chen, B; Evangelou, S; Timotheou, S; (2021) Optimal Motion Control for Connected and Automated Electric Vehicles at Signal-Free Intersections. In: Proceedings of the 2020 59th IEEE Conference on Decision and Control (CDC). (pp. pp. 2831-2836). IEEE: Jeju Island, South Korea. Green open access

[img]
Preview
Text
paper.pdf - Accepted version

Download (1MB) | Preview

Abstract

Traffic congestion is one of the major issues for urban traffic networks. The connected and autonomous vehicles (CAV) is an emerging technology that has the potential to address this issue by improving safety, efficiency, and capacity of the transportation system. In this paper, the problem of optimal trajectory planning of battery-electric CAVs in the context of cooperative crossing of an unsignalized intersection is addressed. An optimization-based centralized intersection controller is proposed to find the optimal velocity trajectory of each vehicle so as to minimize electric energy consumption and traffic throughput. Solving the underlying optimization problem for a group of CAVs is not straightforward because of the nonlinear and nonconvex dynamics, especially when the powertrain model is explicitly modelled. In order to ensure a rapid solution search and a unique global optimum, the optimal control problem (OCP) is reformulated via convex modeling techniques. Several simulation case studies show the effectiveness of the proposed approach and the trade-off between energy consumption and traffic throughput is illustrated.

Type: Proceedings paper
Title: Optimal Motion Control for Connected and Automated Electric Vehicles at Signal-Free Intersections
Event: 2020 59th IEEE Conference on Decision and Control (CDC)
Location: Jeju Island, South Korea
Dates: 14 December 2020 - 18 December 2020
ISBN-13: 978-1-7281-7447-1
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/CDC42340.2020.9304392
Publisher version: https://doi.org/10.1109/CDC42340.2020.9304392
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Mechanical power transmission, Energy consumption, Batteries, Vehicle dynamics, Trajectory, Torque, Safety
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10118036
Downloads since deposit
6Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item