Modeling and Simulation of Interaction Between Road Users at Mixed-traffic Intersections

To accurately describe the interaction and microscopic motion of road users, and provide traffic flow for the virtual testing of autonomous vehicles, this paper develops an interaction model for representing interactions between road users at mixed-traffic intersections. Based on the human cognitive process, the model is designed as a threelayered "perception-decision-action" framework to capture the whole interaction process of road users in mixed traffic. In the perception layer, an interaction selection model is proposed to dynamically decide the interactive road user based on their trajectories. The Decision layer chooses a suitable behavior decision result for road users according to the traffic context. The action layer calculates the behavior trajectory, acceleration, and steering angle based on the decision result to jointly capture the two- dimensional motion of road users. Then, a virtual testing platform is established to verify the performance of the proposed model using the Opendrive road network. Simulation results show that the proposed model can well represent the interaction between different kinds of road users, including motor vehicles, bicycles, and pedestrians. This study provides a way for exploring how to provide traffic flow and satisfy the high precision simulation requirement for virtual testing tools. Copyright © 2022 by Science Press.