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

In: Intelligent Control and Smart Energy Management

Author

Listed:
  • Amaury Hayat

    (Ecole des Ponts Paristech)

  • Xiaoqian Gong

    (Arizona State University)

  • Jonathan Lee

    (University of California at Berkeley)

  • Sydney Truong

    (Rutgers University Camden)

  • Sean McQuade

    (Rutgers University Camden)

  • Nicolas Kardous

    (University of California at Berkeley)

  • Alexander Keimer

    (University of California at Berkeley)

  • Yiling You

    (University of California at Berkeley)

  • Saleh Albeaik

    (University of California at Berkeley)

  • Eugene Vinistky

    (University of California at Berkeley)

  • Paige Arnold

    (Rutgers University Camden)

  • Maria Laura Delle Monache

    (INRIA Grenoble—Rhône Alpes)

  • Alexandre Bayen

    (University of California at Berkeley)

  • Benjamin Seibold

    (Temple University)

  • Jonathan Sprinkle

    (University of Arizona)

  • Dan Work

    (Vanderbilt University)

  • Benedetto Piccoli

    (Rutgers University Camden)

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.

Suggested Citation

  • 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 Monach, 2022. "A Holistic Approach to the Energy-Efficient Smoothing of Traffic via Autonomous Vehicles," Springer Optimization and Its Applications, in: Maude Josée Blondin & João Pedro Fernandes Trovão & Hicham Chaoui & Panos M. Pardalos (ed.), Intelligent Control and Smart Energy Management, pages 285-316, Springer.
    • Handle: RePEc:spr:spochp:978-3-030-84474-5_10
    DOI: 10.1007/978-3-030-84474-5_10
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