Spatially explicit modeling of parking search as a tool for urban parking facilities and policy assessment

Abstract

The engineering view of a measurable, supply-independent, demand for parking that can be expressed by “minimum parking codes” has been generally rejected during the last two decades and is gradually being replaced by “maximum provision” codes, limited parking development, and demand pricing. To assess new planning practices one has to estimate the drivers' reaction to proposed spatial–temporal parking limitations. The paper applies a high-resolution spatially explicit agent-based model termed “PARKAGENT” as a tool for this assessment. The model is used for evaluation of parking demand in the Diamond Exchange area in Ramat Gan, a city in the Tel Aviv metropolitan area, for estimating the effectiveness of planned parking facilities for different development scenarios in the area and assessing electronic signage system that directs drivers to vacant parking lots. The results strongly indicate the advantages of agent-based modeling over the current dominant engineering approach and show the potential benefits of using an intelligent parking guidance system.