Transportation systems in general consist of many agents who choose their behaviors through learning based on their experiences and information provided. The agents interact mutually through the system, and the system must be dynamic and complex. The agent-based simulation is one of the methods for examining such a complex system. The simulation enables us to model the transportation system relatively flexibly. Assuming that agents reason and learn inductively based on their experiences, agent-based transportation system simulation models are developed. Each agent learns how best to choose a route based on his experiences, and the behavior of such agents and the mechanism of the transportation system are examined through simulation experiments.
Nakayama et al. (2008) studied this question.