Game-Theoretic Modeling of Multi-Vehicle Interactions at Uncontrolled Intersections
This work addresses the need for simulation tools to verify autonomous driving systems in mixed traffic, though it is incremental as it builds on existing game-theoretic models with parameterization for intersection layouts.
The authors tackled the problem of modeling vehicle interactions at uncontrolled intersections for autonomous driving simulation, proposing a game-theoretic framework that reproduces real-world scenarios and resolves traffic conflicts with reasonable performance and manageable computational complexity.
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.