Development of a Game Engine-Based Multi-Agent Model to Characterize Human-Autonomous Vehicle Interactions

This study presents the development of a game engine-based traffic microsimulation model that enables users to test and analyze unique transportation scenarios in an interactive 3D environment. The model combines Unity 3D, and SketchUp and scripts to implement built environment, pedestrian and driving behaviors within a game engine simulation framework. The game engine comprises three components: a 3D model for built environment, vehicle game object, and pedestrian game object. C# programming language is utilized to develop scripts within unity to create 3D game-objects, construct infrastructures, and train both static and dynamic game-objects to exhibit required behaviors. This study also deploys the developed model to enhance the understanding of interactions between human-driven vehicles (HVs) and autonomous vehicles (AVs) in mixed traffic scenarios. By examining human drivers’ responses in fully human-driven, fully autonomous, and mixed traffic scenarios, this study highlights the variations in behavior, interaction dynamics, and impacts on safety and performance. Results show that participants perceive higher safety and comfort when following AVs. With higher uptake of AVs, smoother and more predictable driving was observed, reducing near-miss incidents with pedestrians and enhancing overall traffic flow. The game engine developed in this study can potentially facilitate collaboration with researchers and stakeholders, providing design inputs and expert opinions to address planning and engineering challenges in AV operations.