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Book Sections Year : 2019

Feedback control algorithms for the dissipation of traffic waves with autonomous vehicles

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Abstract

This article considers the problem of traffic control in which an autonomous vehicle is used to regulate human piloted traffic to dissipate stop and go traffic waves. We first investigate the controllability of well-known microscopic traffic flow models, namely i) the Bando model (also known as the optimal velocity model), ii) the follow-the-leader model, and iii) a combined optimal velocity follow the leader model. Based on the controllability results, we propose three control strategies for an autonomous vehicle to stabilize the other, human-piloted traffic. We subsequently simulate the control effects on the microscopic models of human drivers in numerical experiments to quantify the potential benefits of the controllers. Based on the simulations, finally we conduct a field experiment with 22 human drivers and a fully autonomous-capable vehicle, to assess the feasibility of autonomous vehicle based traffic control on real human piloted traffic. We show that both in simulation and in the field test that an autonomous vehicle is able to dampen waves generated by 22 cars, and that as a consequence, the total fuel consumption of all vehicles is reduced by up to 20%.
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Dates and versions

hal-01930724 , version 1 (22-11-2018)

Identifiers

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Maria Laura Delle Monache, Thibault Liard, Anais Rat, Raphael E. Stern, Rahul Bhadani, et al.. Feedback control algorithms for the dissipation of traffic waves with autonomous vehicles. Computational Intelligence and Optimization Methods for Control Engineering, Springer, pp.275-299, 2019, ⟨10.1007/978-3-030-25446-9_12⟩. ⟨hal-01930724⟩
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