Game-theoretic Modeling of Traffic in Unsignalized Intersection Network for Autonomous Vehicle Control Verification and Validation
This work addresses the need for simulation tools to verify and validate autonomous vehicle control in mixed traffic environments, but it appears incremental as it applies existing game theory to a specific domain.
The authors tackled the problem of simulating interactions between autonomous and human-driven vehicles at unsignalized intersections by proposing a game-theoretic modeling approach, which they used to test and optimize AV control systems, though no concrete performance numbers were provided.
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.