A PDE-ODE model for traffic control with autonomous vehicles-Reference-Cited by-同舟云学术

A PDE-ODE model for traffic control with autonomous vehicles

Published:2023 Issue:3 Volume:18 Page:1190-1206
ISSN:1556-1801
Container-title:Networks and Heterogeneous Media
language:
Short-container-title:NHM

Author:

Liard Thibault¹,Stern Raphael²,Monache Maria Laura Delle³

Affiliation:

1. Univ. Limoges, CNRS, XLIM, UMR 7252, F-87000 Limoges, France

2. Department of Civil, Environmental, and Geo- Engineering, University of Minnesota, 500 Pillsbury Dr SE, Minneapolis, MN 55406, USA

3. Department of Civil and Environmental Engineering, University of California, Berkeley, Berkeley, CA, 94720, USA

Abstract

<abstract><p>We consider a partial differential equation - ordinary differential equation system to describe the dynamics of traffic flow with autonomous vehicles. In the model, the bulk flow of human drivers is represented by a scalar conservation law, while each autonomous vehicle is described by an ordinary differential equation. The coupled PDE-ODE model is introduced, and existence of solutions for this model is shown, along with a proposed algorithm to construct approximate solutions. Next, we propose a control strategy for the speeds of the autonomous vehicles to minimize the average fuel consumption of the entire traffic flow. Existence of solutions for the optimal control problem is proved, and we numerically show that a reduction in average fuel consumption is possible with an AV acting as a moving bottleneck.</p></abstract>

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

Applied Mathematics,Computer Science Applications,General Engineering,Statistics and Probability

Reference27 articles.

1. K. Ahn, H. Rakha, A. Trani, M. Van Aerde, Estimating vehicle fuel consumption and emissions based on instantaneous speed and acceleration levels, J Transp Eng, 128 (2002), 182–190. https://doi.org/10.1061/(ASCE)0733-947X(2002)128:2(182)

2. I. M. Berry, The effects of driving style and vehicle performance on the real-world fuel consumption of US light-duty vehicles, Doctoral Thesis of Massachusetts Institute of Technology, Cambridge, 2010.

3. C. Chalons, M. L. Delle Monache, P. Goatin, A conservative scheme for non-classical solutions to a strongly coupled pde-ode problem, Interfaces Free. Boundaries, 19 (2017), 553–570. https://doi.org/10.4171/IFB/392

4. M. Čičić, K. H. Johansson, Traffic regulation via individually controlled automated vehicles: a cell transmission model approach, 2018 21st International Conference on Intelligent Transportation Systems (ITSC), (2018), 766–771.

5. S. Cui, B. Seibold, R. Stern, D. B. Work, Stabilizing traffic flow via a single autonomous vehicle: Possibilities and limitations, Proceedings of the IEEE Intelligent Vehicles Symposium, (2017), 1336–1341.

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