Kakuya Matsushima

Agent-Based Modeling Simulation for Economic Evaluation of Parking Guidance Information System in Rest Areas

This paper presents an agent-based approach to evaluating the economic effects of a parking guidance information (PGI) system by modeling drivers’ behavior under different parking guidance conditions: with PGI and without PGI. An agent-based model (ABM) is established to explicitly capture car-following behavior and driver searching behavior under the condition of knowing the characteristics of alternatives and receiving information by PGI system. The parking search process is modeled by using MNL model. The study may be regarded as one of the few studies to integrate multi-agent activities of parking choice process, Poisson distribution, GIS, and a detailed traffic micro-simulation for economic evaluation of with and without PGI system. The simulation results of the number of lost agent, average searching time of all agents can be applied to evaluate the economic benefit of PGI system.