Utilization of Gray Clustering Analysis (GCA) in the modeling of urban public parking site selection (case study: Zoning the 6th district of Tehran)

With the urbanization growth and increasing in vehicle density in the last decades, traffic has become a serious problem in big cities. Public parking as one of the most important urban infrastructure plays an important role in traffic fluency and reduces marginal car parking. The aim of this study is to propose an optimum model for zoning urban areas from the parking deployment utility point of view by using Gray Clustering Analysis. After determining the effective parameters, Fuzzy Analytic Hierarchy Process (FAHP) was used for weighting parking parameters. The purpose of the study is to assess current public parking conditions and suggest some places for future development, in the 6th district of Tehran that has a lot of traveling attraction places and plays a Cross-region role. The model assessed based on field observations and gamma coefficient used to determine the similarity between the results of model and field observations. The gamma coefficient was 0.904 that shows strong relationship between them. The results of this study indicated the fact that the use of Gray Clustering model in the zoning and site based decision-making, along with GIS analysis functions, is very accurate.