Game-theoretic Modeling of Traffic in Unsignalized Intersection Network for Autonomous Vehicle Control Verification and Validation
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Abstract (arXiv)
For a foreseeable future, autonomous vehicles (AVs) will operate in traffic together with human-driven vehicles. Their planning and control systems need extensive testing, including early-stage testing in simulations where the interactions among autonomous/human-driven vehicles are represented. Motivated by the need for such simulation tools, we propose a game-theoretic approach to modeling vehicle interactions, in particular, for urban traffic environments with unsignalized intersections. We develop traffic models with heterogeneous (in terms of their driving styles) and interactive vehicles based on our proposed approach, and use them for virtual testing, evaluation, and calibration of AV control systems. For illustration, we consider two AV control approaches, analyze their characteristics and performance based on the simulation results with our developed traffic models, and optimize the parameters of one of them.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 16 Oct 2019.
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Citing papers per year: 2021: 2; 2022: 0; 2023: 1; 2024: 4; 2025: 1.
8 papers.
- 2024Reward-Driven Automated Curriculum Learning for Interaction-Aware Self-Driving at Unsignalized Intersectionscited by 8
- 2024Autonomous Driving at Unsignalized Intersections: A Review of Decision-Making Challenges and Reinforcement Learning-Based Solutionscited by 7
- 2021Learning Human Rewards by Inferring Their Latent Intelligence Levels in Multi-Agent Games: A Theory-of-Mind Approach with Application to Driving Datacited by 6
- 2025Bilevel Multi-Armed Bandit-Based Hierarchical Reinforcement Learning for Interaction-Aware Self-Driving at Unsignalized Intersectionscited by 4
- 2023IR-STP: Enhancing Autonomous Driving with Interaction Reasoning in Spatio-Temporal Planningcited by 2
- 2024A Conflicts-free, Speed-lossless KAN-based Reinforcement Learning Decision System for Interactive Driving in Roundaboutscited by 1
- 2021Energy-Efficient Autonomous Driving Using Cognitive Driver Behavioral Models and Reinforcement Learningcited by 0
- 2024Autonomous Vehicle Decision-Making Framework for Considering Malicious Behavior at Unsignalized Intersectionscited by 0
- 2025Bilevel Multi-Armed Bandit-Based Hierarchical Reinforcement Learning for Interaction-Aware Self-Driving at Unsignalized Intersections6 Feb 2025
- 2024Autonomous Driving at Unsignalized Intersections: A Review of Decision-Making Challenges and Reinforcement Learning-Based Solutions20 Sep 2024
- 2024Autonomous Vehicle Decision-Making Framework for Considering Malicious Behavior at Unsignalized Intersections11 Sep 2024
- 2024A Conflicts-free, Speed-lossless KAN-based Reinforcement Learning Decision System for Interactive Driving in Roundabouts15 Aug 2024
- 2024Reward-Driven Automated Curriculum Learning for Interaction-Aware Self-Driving at Unsignalized Intersections20 Mar 2024
- 2023IR-STP: Enhancing Autonomous Driving with Interaction Reasoning in Spatio-Temporal Planning6 Nov 2023
- 2021Energy-Efficient Autonomous Driving Using Cognitive Driver Behavioral Models and Reinforcement Learning27 Nov 2021
- 2021Learning Human Rewards by Inferring Their Latent Intelligence Levels in Multi-Agent Games: A Theory-of-Mind Approach with Application to Driving Data7 Mar 2021