Dissipation of stop-and-go waves via control of autonomous vehicles: Field experiments

Raphael E Stern, Shumo Cui, Maria Laura Delle Monache, Rahul Bhadani, Matt Bunting, Miles Churchill, Nathaniel Hamilton, R'mani Haulcy, Hannah Pohlmann, Fangyu Wu, Benedetto Piccoli, Benjamin Seibold, Jonathan Sprinkle, Daniel B. Work

Research output: Contribution to journalArticlepeer-review

148 Scopus citations

Abstract

Traffic waves are phenomena that emerge when the vehicular density exceeds a critical threshold. Considering the presence of increasingly automated vehicles in the traffic stream, a number of research activities have focused on the influence of automated vehicles on the bulk traffic flow. In the present article, we demonstrate experimentally that intelligent control of an autonomous vehicle is able to dampen stop-and-go waves that can arise even in the absence of geometric or lane changing triggers. Precisely, our experiments on a circular track with more than 20 vehicles show that traffic waves emerge consistently, and that they can be dampened by controlling the velocity of a single vehicle in the flow. We compare metrics for velocity, braking events, and fuel economy across experiments. These experimental findings suggest a paradigm shift in traffic management: flow control will be possible via a few mobile actuators (less than 5%) long before a majority of vehicles have autonomous capabilities.

Original languageEnglish (US)
Pages (from-to)205-221
Number of pages17
JournalTransportation Research Part C: Emerging Technologies
Volume89
DOIs
StatePublished - Apr 2018
Externally publishedYes

Bibliographical note

Funding Information:
This material is based upon work supported by the U.S. National Science Foundation under Grant No. CNS-1446715 (B.P.), CNS-1446690 (B.S.), CNS-1446435 (J.S.), and CNS-1446702 (D.W.). The authors thank the University of Arizona Motor Pool in providing the vehicle fleet. They offer additional special thanks for the services of N. Emptage in carrying out the experiment logistics.

Funding Information:
This material is based upon work supported by the U.S. National Science Foundation under Grant No. CNS-1446715 (B.P.), CNS-1446690 (B.S.), CNS-1446435 (J.S.), and CNS-1446702 (D.W.). The authors thank the University of Arizona Motor Pool in providing the vehicle fleet. They offer additional special thanks for the services of N. Emptage in carrying out the experiment logistics.

Publisher Copyright:
© 2018 Elsevier Ltd

Keywords

  • Autonomous vehicles
  • Traffic control
  • Traffic waves

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