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Improving Urban Traffic Throughput With Vehicle Platooning: Theory and Experiments

Authors :
Stanley W. Smith
Yeojun Kim
Jacopo Guanetti
Ruolin Li
Roya Firoozi
Bruce Wootton
Alexander A. Kurzhanskiy
Francesco Borrelli
Roberto Horowitz
Murat Arcak
Source :
IEEE Access, Vol 8, Pp 141208-141223 (2020)
Publication Year :
2020
Publisher :
IEEE, 2020.

Abstract

In this paper we present a model-predictive control (MPC) based approach for vehicle platooning in an urban traffic setting. Our primary goal is to demonstrate that vehicle platooning has the potential to significantly increase throughput at intersections, which can create bottlenecks in the traffic flow. To do so, our approach relies on vehicle connectivity: vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. In particular, we introduce a customized V2V message set which features a velocity forecast, i.e. a prediction on the future velocity trajectory, which enables platooning vehicles to accurately maintain short following distances, thereby increasing throughput. Furthermore, V2I communication allows platoons to react immediately to changes in the state of nearby traffic lights, e.g. when the traffic phase becomes green, enabling additional gains in traffic efficiency. We present our design of the vehicle platooning system, and then evaluate performance by estimating the potential gains in terms of throughput using our results from simulation, as well as experiments conducted with real test vehicles on a closed track. Lastly, we briefly overview our demonstration of vehicle platooning on public roadways in Arcadia, CA.

Details

Language :
English
ISSN :
21693536
Volume :
8
Database :
Directory of Open Access Journals
Journal :
IEEE Access
Publication Type :
Academic Journal
Accession number :
edsdoj.77b89ecb9e1945639aa8a969b7ec0664
Document Type :
article
Full Text :
https://doi.org/10.1109/ACCESS.2020.3012618