Feedback Control Algorithms for the Dissipation of Traffic Waves with Autonomous Vehicles

  • Maria Laura Delle Monache
  • Thibault Liard
  • Anaïs Rat
  • Raphael Stern
  • Rahul Bhadani
  • Benjamin Seibold
  • Jonathan Sprinkle
  • Daniel B. Work
  • Benedetto PiccoliEmail author
Part of the Springer Optimization and Its Applications book series (SOIA, volume 150)


This article considers the problem of traffic control in which an autonomous vehicle is used to regulate human-piloted traffic to dissipate stop-and-go traffic waves. We first investigated the controllability of well-known microscopic traffic flow models, namely, (i) the Bando model (also known as the optimal velocity model), (ii) the follow-the-leader model, and (iii) a combined optimal velocity follow-the-leader model. Based on the controllability results, we proposed three control strategies for an autonomous vehicle to stabilize the other, human-piloted traffics. We subsequently simulate the control effects on the microscopic models of human drivers in numerical experiments to quantify the potential benefits of the controllers. Based on the simulations, finally, we conduct a field experiment with 22 human drivers and a fully autonomous-capable vehicle, to assess the feasibility of autonomous vehicle-based traffic control on real human-piloted traffic. We show that both in simulation and in the field test that an autonomous vehicle is able to dampen waves generated by 22 cars, and that as a consequence, the total fuel consumption of all vehicles is reduced by up to 20%.



This research was supported by the Inria associated team "ModEling autonoMous vEhicles iN Traffic flOw " (MEMENTO). This material is based upon work supported by the National Science Foundation under Grant No. CNS-1446715 (Piccoli), CNS-1446690 (Seibold), CNS-1446435 (Sprinkle), and CNS-1446702 (Work). The authors thank Hannah Pohlmann for her help in designing and tuning of the Follow-the-Leader-Bando microscopic model.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Maria Laura Delle Monache
    • 1
  • Thibault Liard
    • 1
  • Anaïs Rat
    • 2
  • Raphael Stern
    • 3
  • Rahul Bhadani
    • 4
  • Benjamin Seibold
    • 5
  • Jonathan Sprinkle
    • 4
  • Daniel B. Work
    • 3
  • Benedetto Piccoli
    • 2
    Email author
  1. 1.University of Grenoble Alpes, Inria, CNRS, Grenoble INP, GIPSA-LabGrenobleFrance
  2. 2.Department of MathematicsUniversity of RutgersCamdenUSA
  3. 3.Department of Civil and Environmental EngineeringInstitute for Software Integrated Systems, Vanderbilt UniversityNashvilleUSA
  4. 4.Department of Electrical and Computer EngineeringUniversity of ArizonaTucsonUSA
  5. 5.Department of MathematicsTemple UniversityPhiladelphiaUSA

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