Game Theory-Based Traffic Modeling for Calibration of Automated Driving Algorithms

  • Nan LiEmail author
  • Mengxuan Zhang
  • Yildiray Yildiz
  • Ilya Kolmanovsky
  • Anouck Girard
Part of the Lecture Notes in Control and Information Sciences book series (LNCIS, volume 476)


Automated driving functions need to be validated and calibrated so that a self-driving car can operate safely and efficiently in a traffic environment where interactions between it and other traffic participants constantly occur. In this paper, we describe a traffic simulator capable of representing vehicle interactions in traffic developed based on a game-theoretic traffic model. We demonstrate its functionality for parameter optimization in automated driving algorithms by designing a rule-based highway driving algorithm and calibrating the parameters using the traffic simulator.



Nan Li and Ilya Kolmanovsky acknowledge the support of this research by the National Science Foundation under Award CNS 1544844 to the University of Michigan. Yildiray Yildiz acknowledges the support of this research by the Scientific and Technological Research Council of Turkey under Grant 114E282 to Bilkent University.


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Nan Li
    • 1
    Email author
  • Mengxuan Zhang
    • 1
  • Yildiray Yildiz
    • 2
  • Ilya Kolmanovsky
    • 1
  • Anouck Girard
    • 1
  1. 1.Department of Aerospace EngineeringUniversity of MichiganAnn ArborUSA
  2. 2.Department of Mechanical EngineeringBilkent UniversityAnkaraTurkey

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