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Benefits of routing and replanning with imperfect information

Equilibrium-based traffic assignment models do not consider traffic movement. In particular the functions that are used to estimate delay from volume of vehicles do not allow the representation of the phenomenon of congestion spillback. In some cases one needs to understand and analyze microscopic properties associated to how travelers adjust to the conditions they encounter. This, on its turn, leads to dynamic environments that are difficult to analyze with conventional tools. This paper presents an agent-based simulation of route choice under different conditions of demand generation, number, and types of driver agents. We consider more sophisticated drivers' behaviors such as en-route decision-making. Besides, they may be equipped with vehicle-to-vehicle communication. We discuss the effects of the use of: various ratio demand/capacity, demand generation, information exchange, and re-planning strategies. The use of an agent-based approach allows the analysis of different classes of agents, thus departing from the investigation of population-wide metrics only. 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. However, in general, having imperfect information is advantageous, especially from the whole system perspective.