An Agent-Based Simulation Model for Parking Variable Message Sign Location Problem

Abstract

Parking spaces are often in short supply in urban areas. To balance the supply and demand and alleviate the overconsumption of public spaces, parking variable message signs (parking VMSs) are commonly used to release information on space availability to drivers en route. The aim of this study was to find the optimal positions for parking VMSs. To achieve the objective, we first define the major decision point (MDP) as the intersection where the newly generated path deviates from the previous one. When informed that the target parking lot is fully occupied, the driver would divert to an alternative one. The route to the alternative parking lot is indicated as the newly generated path, while the one leading to the original parking lot is denoted as the previous one. Quantitatively, MDPs with the highest frequency of occurrence are selected as the candidate positions. Then, an agent-based simulation is proposed to identify the MDPs induced by changes of space availability and the selection of routes. The results indicate that the proposed location algorithm slightly outperforms the scheme with the completed parking information in terms of average travel time and average travel distance. The algorithm can be further integrated into a simulation package, which may assist in the design and operation of an urban parking guidance and information system.