Agent-based simulation of mobility in real-world transportation networks: effects of acquiring information and replanning en-route

Macroscopic and equilibrium-based models for traffic assignment and simulation disregard many details of traffic movement. For some applications, one needs to understand and analyze microscopic properties. This paper discusses an agent-based simulation of route choice under different conditions of demand generation, number, and types of travelers. The effects of en-route decision-making and vehicle-tovehicle communication were tested in a real-world scenario. The analysis has considered different classes of travelers, which is only possible if a microscopic, agent-based simulation is used. The main conclusion is that for travelers whose trips are long, there is a benefit of using communication and replan en-route, depending on the demand volume.