A Game Theory-Based Approach for Modeling Autonomous Vehicle Behavior in Congested, Urban Lane-Changing Scenarios

Smirnov, Nikita; Liu, Yuzhou; Validi, Aso; Morales-Alvarez, Walter; Olaverri-Monreal, Cristina

doi:10.3390/s21041523

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A Game Theory-Based Approach for Modeling Autonomous Vehicle Behavior in Congested, Urban Lane-Changing Scenarios

Nikita Smirnov

^1,2,*

Yuzhou Liu

¹,

Aso Validi

Walter Morales-Alvarez

and

Cristina Olaverri-Monreal

^1,*

Chair ITS-Sustainable Transport Logistics 4.0, Johannes Kepler University, 4040 Linz, Austria

Department of Communications Technology, Ural Federal University, 620078 Yekaterinburg, Russia

Authors to whom correspondence should be addressed.

Academic Editors: Ignacio Parra Alonso, Noelia Hernández Parra, Iván García Daza, Augusto Luis Ballardini and David Fernández-Llorca

Sensors 2021, 21(4), 1523; https://doi.org/10.3390/s21041523

Received: 25 January 2021 / Revised: 16 February 2021 / Accepted: 18 February 2021 / Published: 22 February 2021

(This article belongs to the Special Issue Sensors Technologies for Intelligent Transportation Systems)

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Abstract

Autonomous vehicles are expected to display human-like behavior, at least to the extent that their decisions can be intuitively understood by other road users. If this is not the case, the coexistence of manual and autonomous vehicles in a mixed environment might affect road user interactions negatively and might jeopardize road safety. To this end, it is highly important to design algorithms that are capable of analyzing human decision-making processes and of reproducing them. In this context, lane-change maneuvers have been studied extensively. However, not all potential scenarios have been considered, since most works have focused on highway rather than urban scenarios. We contribute to the field of research by investigating a particular urban traffic scenario in which an autonomous vehicle needs to determine the level of cooperation of the vehicles in the adjacent lane in order to proceed with a lane change. To this end, we present a game theory-based decision-making model for lane changing in congested urban intersections. The model takes as input driving-related parameters related to vehicles in the intersection before they come to a complete stop. We validated the model by relying on the Co-AutoSim simulator. We compared the prediction model outcomes with actual participant decisions, i.e., whether they allowed the autonomous vehicle to drive in front of them. The results are promising, with the prediction accuracy being 100% in all of the cases in which the participants allowed the lane change and 83.3% in the other cases. The false predictions were due to delays in resuming driving after the traffic light turned green. View Full-Text

Keywords: game theory; lane change; traffic jam; intelligent transport systems

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Smirnov, N.; Liu, Y.; Validi, A.; Morales-Alvarez, W.; Olaverri-Monreal, C. A Game Theory-Based Approach for Modeling Autonomous Vehicle Behavior in Congested, Urban Lane-Changing Scenarios. Sensors 2021, 21, 1523. https://doi.org/10.3390/s21041523

AMA Style

Smirnov N, Liu Y, Validi A, Morales-Alvarez W, Olaverri-Monreal C. A Game Theory-Based Approach for Modeling Autonomous Vehicle Behavior in Congested, Urban Lane-Changing Scenarios. Sensors. 2021; 21(4):1523. https://doi.org/10.3390/s21041523

Chicago/Turabian Style

Smirnov, Nikita, Yuzhou Liu, Aso Validi, Walter Morales-Alvarez, and Cristina Olaverri-Monreal. 2021. "A Game Theory-Based Approach for Modeling Autonomous Vehicle Behavior in Congested, Urban Lane-Changing Scenarios" Sensors 21, no. 4: 1523. https://doi.org/10.3390/s21041523

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Author Biographies

Nikita Smirnov

Nikita Smirnov graduated with a master’s degree in design and technology of electronic appliances from Ural Federal University, Russia. He is currently working as a university assistant at the Chair ITS-Sustainable Transport Logistics 4.0 at JKU in Austria and he is a PhD student at the Ural Federal University.

Yuzhou Liu

Yuzhou Liu graduated in 2018 from the University of Applied Sciences Technikum Wien. He is a graduate student and a student research assistant at the Johannes Kepler University, at the Chair ITS-Sustainable Transport Logistics 4.0. His research focuses on the simulation of intelligent transport systems. He has published in conferences such as the IEEE Intelligent Vehicle Symposium. His research interests include autonomous driving, last mile delivery, and machine learning.

Aso Validi

Aso Validi graduated with a master’s degree in intelligent transport systems from the University of Applied Sciences Technikum Wien in Austria in 2016. She also holds a bachelor's degree in civil engineering from the Azad University of Sanandaj in Kurdistan, Iran. She is currently pursuing a Ph.D. degree at Johannes Kepler University in Linz and working as an university assistant at the Chair ITS-Sustainable Transport Logistics 4.0.

Walter Morales-Alvarez

Walter Morales-Alvarez graduated in 2018 from the Simon Bolivar University in Caracas as an electronic engineer. He is a PhD student at the Johannes Kepler University, where he is working as a university assistant at the Chair ITS-Sustainable Transport Logistics 4.0. His research focuses on the field of intelligent transport systems. He has published in conferences such as the IEEE International Conference on Intelligent Transport Systems and the IEEE Intelligent Vehicle Symposium. His research interests include autonomous driving, human–machine interaction, and deep learning.

Cristina Olaverri-Monreal

Cristina Olaverri-Monreal holds a position as a full professor and BMK-endowed Chair of Sustainable Transport Logistics 4.0 at the Johannes Kepler University Linz in Austria. She received her PhD from the Ludwig-Maximilians University (LMU) in Munich in cooperation with BMW. Her research aims are studying solutions for efficient and effective transportation, focusing on minimizing the barrier between users and road systems. To this end, she relies on automation, wireless communication, and sensing technologies that pertain to the field of intelligent transportation systems (ITS). Dr. Olaverri is president-elect of the IEEE ITS Society Executive Committee, chair of the IEEE ITS Austrian Chapter, and chair of the Technical Activities Committee (TAC) on Human Factors in ITS. This TAC was recognized with the award "best TAC of the IEEE ITSS" in both 2018 and 2019. In addition, she serves as an associate editor and editorial board member of several journals in the field, including the "IEEE Transactions on Intelligent Transportation Systems" and "IEEE Intelligent Transportation Systems Magazine (ITSM)". She was recently recognized for her dedicated contribution to continuing education in the field of ITS with the 2017 IEEE Educational Activities Board Meritorious Achievement Award in Continuing Education.

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A Game Theory-Based Approach for Modeling Autonomous Vehicle Behavior in Congested, Urban Lane-Changing Scenarios

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