Game-theoretic Modeling of Traffic in Unsignalized Intersection Network for Autonomous Vehicle Control Verification and Validation

TL;DR

This paper introduces a game-theoretic traffic modeling approach for simulating interactions among autonomous and human-driven vehicles at unsignalized intersections, aiding in AV control system testing and validation.

Contribution

It presents a novel game-theoretic framework for modeling heterogeneous vehicle interactions in urban traffic, enabling improved simulation and evaluation of autonomous vehicle control systems.

Findings

Developed traffic models for heterogeneous vehicle interactions.

Analyzed and compared two AV control approaches.

Optimized parameters of one control approach based on simulation results.

Abstract

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.