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A Holistic Approach to the Energy-Efficient Smoothing of Traffic via Autonomous Vehicles

  • Amaury Hayat
  • , Xiaoqian Gong
  • , Jonathan Lee
  • , Sydney Truong
  • , Sean McQuade
  • , Nicolas Kardous
  • , Alexander Keimer
  • , Yiling You
  • , Saleh Albeaik
  • , Eugene Vinistky
  • , Paige Arnold
  • , Maria Laura Delle Monache
  • , Alexandre Bayen
  • , Benjamin Seibold
  • , Jonathan Sprinkle
  • , Dan Work
  • , Benedetto Piccoli
  • Arizona State University
  • University of California, Berkeley
  • Rutgers University–Camden
  • INRIA Institut National de Recherche en Informatique et en Automatique
  • Temple University
  • University of Arizona
  • Vanderbilt University

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

12 Citations (Scopus)

Abstract

The technological advancements in terms of vehicle on-board sensors and actuators, as well as for infrastructures, open an unprecedented scenario for the management of vehicular traffic. We focus on the problem of smoothing traffic by controlling a small number of autonomous vehicles immersed in the bulk traffic stream. Specifically, we aim at dissipating stop-and-go waves, which are ubiquitous and proven to increase fuel consumption tremendously and reduce. Our approach is holistic, as it is based on a large collaborative effort, which ranges from mathematical models for traffic and control all the way to building infrastructures capable of measuring energy efficiency and providing real-time data. Such an approach allows to clearly set and measure a metric for success in the form of a reduction of at least 10% of fuel consumption using 5% of autonomous vehicles immersed in bulk traffic. The chapter illustrates the overall approach and provides simulation results on a tuned microsimulator for the California I-210.

Original languageEnglish
Title of host publicationSpringer Optimization and Its Applications
PublisherSpringer
Pages285-316
Number of pages32
DOIs
Publication statusPublished - 1 Jan 2022

Publication series

NameSpringer Optimization and Its Applications
Volume181
ISSN (Print)1931-6828
ISSN (Electronic)1931-6836

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

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