Game-Theoretic Modeling of Multi-Vehicle Interactions at Uncontrolled Intersections
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Abstract (arXiv)
Motivated by the need to develop simulation tools for verification and validation of autonomous driving systems operating in traffic consisting of both autonomous and human-driven vehicles, we propose a framework for modeling vehicle interactions at uncontrolled intersections. The proposed interaction modeling approach is based on game theory with multiple concurrent leader-follower pairs, and accounts for common traffic rules. We parameterize the intersection layouts and geometries to model uncontrolled intersections with various configurations, and apply the proposed approach to model the interactive behavior of vehicles at these intersections. Based on simulation results in various traffic scenarios, we show that the model exhibits reasonable behavior expected in traffic, including the capability of reproducing scenarios extracted from real-world traffic data and reasonable performance in resolving traffic conflicts. The model is further validated based on the level-of-service traffic quality rating system and demonstrates manageable computational complexity compared to traditional multi-player game-theoretic models.
Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). First posted on arXiv 10 Apr 2019.
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Citing papers per year: 2021: 2; 2022: 1; 2023: 1; 2024: 2; 2025: 4; 2026: 1.
11 papers.
- 2021Autonomous Driving Strategies at Intersections: Scenarios, State-of-the-Art, and Future Outlookscited by 15
- 2024Autonomous Driving at Unsignalized Intersections: A Review of Decision-Making Challenges and Reinforcement Learning-Based Solutionscited by 7
- 2023IR-STP: Enhancing Autonomous Driving with Interaction Reasoning in Spatio-Temporal Planningcited by 2
- 2025Game-Theoretic Modeling of Vehicle Unprotected Left Turns Considering Drivers' Bounded Rationalitycited by 1
- 2025An Evolving Scenario Generation Method based on Dual-modal Driver Model Trained by Multi-Agent Reinforcement Learningcited by 1
- 2025Driving is a Game: Combining Planning and Prediction with Bayesian Iterative Best Responsecited by 1
- 2021Energy-Efficient Autonomous Driving Using Cognitive Driver Behavioral Models and Reinforcement Learningcited by 0
- 2022Modeling Human Driver Interactions Using an Infinite Policy Space Through Gaussian Processescited by 0
- 2024Foundation Models for Rapid Autonomy Validationcited by 0
- 2025VLM as Strategist: Adaptive Generation of Safety-critical Testing Scenarios via Guided Diffusioncited by 0
- 2026TSC: Topology-Conditioned Stackelberg Coordination for Multi-Agent Reinforcement Learning in Interactive Drivingcited by 0
- 2026TSC: Topology-Conditioned Stackelberg Coordination for Multi-Agent Reinforcement Learning in Interactive Driving27 Feb 2026
- 2025Driving is a Game: Combining Planning and Prediction with Bayesian Iterative Best Response3 Dec 2025
- 2025VLM as Strategist: Adaptive Generation of Safety-critical Testing Scenarios via Guided Diffusion2 Dec 2025
- 2025An Evolving Scenario Generation Method based on Dual-modal Driver Model Trained by Multi-Agent Reinforcement Learning4 Aug 2025
- 2025Game-Theoretic Modeling of Vehicle Unprotected Left Turns Considering Drivers' Bounded Rationality2 Jul 2025
- 2024Foundation Models for Rapid Autonomy Validation22 Oct 2024
- 2024Autonomous Driving at Unsignalized Intersections: A Review of Decision-Making Challenges and Reinforcement Learning-Based Solutions20 Sep 2024
- 2023IR-STP: Enhancing Autonomous Driving with Interaction Reasoning in Spatio-Temporal Planning6 Nov 2023
- 2022Modeling Human Driver Interactions Using an Infinite Policy Space Through Gaussian Processes3 Jan 2022
- 2021Energy-Efficient Autonomous Driving Using Cognitive Driver Behavioral Models and Reinforcement Learning27 Nov 2021
- 2021Autonomous Driving Strategies at Intersections: Scenarios, State-of-the-Art, and Future Outlooks24 Jun 2021