Impact of autonomous vehicles on traffic management: Case of dynamic lane reversal

Melissa Duell, Michael W. Levin, Stephen D. Boyles, S. Travis Waller

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

As the future of autonomous vehicles (AVs) becomes more certain, transport network managers may seek ways to reinvent elements of the traffic network to improve efficiency. One possibility is dynamic lane reversal, in which the network operator makes use of AV communications and behavior to change the direction of flow on a road link at smaller time intervals than would be possible with human drivers. Although there is much research into the mechanical details of AVs, this study motivates the need for future research by focusing on a planning application in which AVs are already present. A novel extension to an established system optimal dynamic traffic assignment model based on the cell transmission model was examined. The model determined the optimal lane configuration at small space-time intervals. Results demonstrate the model on a single link and a grid network and explore the dynamic demand scenarios that are most conducive to increasing system efficiency with dynamic lane reversal.

Original languageEnglish (US)
Pages (from-to)87-94
Number of pages8
JournalTransportation Research Record
Volume2567
DOIs
StatePublished - 2016

Bibliographical note

Publisher Copyright:
© 2016, National Research Council. All rights reserved.

Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.

Fingerprint Dive into the research topics of 'Impact of autonomous vehicles on traffic management: Case of dynamic lane reversal'. Together they form a unique fingerprint.

Cite this