Abstract
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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Anderson, J.M., Nidhi, K., Stanley, K.D., Sorensen, P., Samaras, C., Oluwatola, O.A.: Autonomous Vehicle Technology: A Guide for Policymakers. Rand Corporation (2014)
Campbell, M., Egerstedt, M., How, J.P., Murray, R.M.: Autonomous driving in urban environments: approaches, lessons and challenges. Philos. Trans. R. Soc. Lond. A Math. Phys. Eng. Sci. 368(1928), 4649–4672 (2010)
Costa-Gomes, M.A., Crawford, V.P.: Cognition and behavior in two-person guessing games: an experimental study. Am. Econ. Rev. 96(5), 1737–1768 (2006)
Costa-Gomes, M.A., Crawford, V.P., Iriberri, N.: Comparing models of strategic thinking in van huyck, battalio, and beil’s coordination games. J. Eur. Econ. Assoc. 7(2–3), 365–376 (2009)
Hedden, T., Zhang, J.: What do you think I think you think? Strategic reasoning in matrix games. Cognition 85(1), 1–36 (2002)
Jaakkola, T., Singh, S.P., Jordan, M.I.: Reinforcement learning algorithm for partially observable markov decision problems. In: Advances in Neural Information Processing Systems, pp. 345–352. Citeseer (1995)
Kikuchi, S., Chakroborty, P.: Car-following model based on fuzzy inference system. Transp. Res. Rec. 82–82 (1992)
Langari, R.: Autonomous vehicles. In: 2017 American Control Conference (ACC), pp. 4018–4022 (2017). https://doi.org/10.23919/ACC.2017.7963571
Li, N., Oyler, D., Zhang, M., Yildiz, Y., Girard, A., Kolmanovsky, I.: Hierarchical reasoning game theory based approach for evaluation and testing of autonomous vehicle control systems. In: IEEE 55th Conference on Decision and Control (CDC), pp. 727–733. IEEE (2016)
Li, N., Oyler, D.W., Zhang, M., Yildiz, Y., Kolmanovsky, I., Girard, A.R.: Game theoretic modeling of driver and vehicle interactions for verification and validation of autonomous vehicle control systems. IEEE Trans. Control Syst. Technol. 99, 1–16 (2017). https://doi.org/10.1109/TCST.2017.2723574
Maurer, M., Gerdes, J.C., Lenz, B., Winner, H.: Autonomous driving: Technical, Legal and Social Aspects. Springer Publishing Company, Incorporated (2016)
McDonald, M., Wu, J., Brackstone, M.: Development of a fuzzy logic based microscopic motorway simulation model. In: IEEE Conference on Intelligent Transportation System, pp. 82–87. IEEE (1997)
Musavi, N., Onural, D., Gunes, K., Yildiz, Y.: Unmanned aircraft systems airspace integration: a game theoretical framework for concept evaluations. J. Guidance Control Dyn. 40(1), 96–109 (2016)
Oyler, D.W., Yildiz, Y., Girard, A.R., Li, N.I., Kolmanovsky, I.V.: A game theoretical model of traffic with multiple interacting drivers for use in autonomous vehicle development. In: 2016 American Control Conference (ACC), pp. 1705–1710 (2016)
Stahl, D.O., Wilson, P.W.: On players models of other players: theory and experimental evidence. Games Econ. Behav. 10(1), 218–254 (1995)
Urmson, C., Anhalt, J., Bagnell, D., Baker, C., Bittner, R., Clark, M., Dolan, J., Duggins, D., Galatali, T., Geyer, C., et al.: Autonomous driving in urban environments: Boss and the urban challenge. J. Field Rob. 25(8), 425–466 (2008)
Yildiz, Y., Agogino, A., Brat, G.: Predicting pilot behavior in medium-scale scenarios using game theory and reinforcement learning. J. Guidance Control Dyn. 37(4), 1335–1343 (2014)
Zhou, J., Schmied, R., Sandalek, A., Kokal, H., del Re, L.: A framework for virtual testing of ADAS. SAE Int. J. Passeng. Cars Electron. Electr. Syst. 9(2016-01-0049), 66–73 (2016)
Acknowledgements
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.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer International Publishing AG, part of Springer Nature
About this chapter
Cite this chapter
Li, N., Zhang, M., Yildiz, Y., Kolmanovsky, I., Girard, A. (2019). Game Theory-Based Traffic Modeling for Calibration of Automated Driving Algorithms. In: Waschl, H., Kolmanovsky, I., Willems, F. (eds) Control Strategies for Advanced Driver Assistance Systems and Autonomous Driving Functions . Lecture Notes in Control and Information Sciences, vol 476. Springer, Cham. https://doi.org/10.1007/978-3-319-91569-2_5
Download citation
DOI: https://doi.org/10.1007/978-3-319-91569-2_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-91568-5
Online ISBN: 978-3-319-91569-2
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)