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Traffic Smoothing Using Explicit Local Controllers: Experimental Evidence for Dissipating Stop-and-go Waves with a Single Automated Vehicle in Dense Traffic

  • Amaury Hayat
  • , Arwa Alanqary
  • , Rahul Bhadani
  • , Christopher Denaro
  • , Ryan J. Weightman
  • , Shengquan Xiang
  • , Jonathan W. Lee
  • , Matthew Bunting
  • , Anish Gollakota
  • , Matthew W. Nice
  • , Derek Gloudemans
  • , Gergely Zachar
  • , Jon F. Davis
  • , Maria Laura Delle Monache
  • , Benjamin Seibold
  • , Alexandre M. Bayen
  • , Jonathan Sprinkle
  • , Daniel B. Work
  • , Benedetto Piccoli
  • Vanderbilt University School of Engineering
  • University of California, Berkeley
  • University of Alabama in Huntsville
  • Rutgers University–Camden
  • Center for Computational and Integrative Biology
  • Tsinghua University
  • University of California
  • University of California
  • Temple University
  • Vanderbilt University

Résultats de recherche: Contribution à un journalArticleRevue par des pairs

9 Citations (Scopus)

Résumé

This article presents experimental evidence of the ability of a single automated vehicle acting as a controller to effectively dissipate stop-and-go waves in real traffic. The automated vehicle succeeded in stabilizing the speed profile by reducing oscillations in time and speed variations between vehicles during rush hour on I-24 in the Nashville area. We detail the control design, deployment and results obtained in this experiment, conducted as part of the CIRCLES consortium's "MegaVanderTest"2022, which involved a total of 100 automated vehicles.

langue originaleAnglais
Pages (de - à)95-110
Nombre de pages16
journalIEEE Control Systems
Volume45
Numéro de publication1
Les DOIs
étatPublié - 1 janv. 2025
Modification externeOui

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