Improving Urban Traffic Throughput with Vehicle Platooning: Theory and Experiments

TL;DR

This paper proposes a model-predictive control approach for vehicle platooning in urban traffic, utilizing vehicle connectivity and communication to increase intersection throughput, demonstrated through simulations and real-world experiments.

Contribution

It introduces a novel V2V message set with velocity forecasting and integrates V2I communication for improved traffic flow in urban environments.

Findings

Significant increase in intersection throughput demonstrated in simulations.

Successful real-vehicle platooning experiments on a closed track.

Potential for improved urban traffic efficiency through connectivity-enabled platooning.

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.