A New Perspective of Traffic Assignment: A Game Theoretical Approach

Abstract

Traditional equilibrium models consider transportation networks with well-defined link travel time functions and continuous drivers. Recently, researchers focused on adding the behavioral dimension lacking in traditional equilibrium models by treating drivers as individual decision-makers (atomic drivers). However, there is currently no underpinning theory that supports the shift from macroscopic to microscopic traffic assignment modeling.
In this paper, a game theoretical model which provides this link is presented. We will show that this model describe drivers' adaptive behaviors as they perform day-to-day route choices. Drivers acquire payoffs with unknown noise of their chosen and alternative routes. This scenario describes a transportation network with the presence of a Traffic Management Center (TMC).
Finally, a simulation-based dynamic traffic assignment simulation is carried out to validate the model using the Simulation of Urban MObility (SUMO) open source software. The simulation shows that Nash equilibrium can be achieved almost surely.