Evaluating the Need for Public Parking in Urban Areas by Using Mathematical and Statistical models, Case Study: Kerman City

The 20th century has caused a great deal of growth and development for the countries of the world، of which was the development of industry and technology، urbanity، and car entrance to people’s life which continues in 21 century. Urban life is influenced by a lot of challenges such as urban transportation، the increase of private car، traffic، parking deficiency and parking place of vehicles. Large cities are faced with two major problems in the field of urban transportation: 1- Ever- increasing of vehicles especially private vehicles 2- Parking deficiency. Large cities and metropolis are faced with more difficulties in this field. kerman city has a lot of difficulties in the field of transportation due to dense population، concentration of urban activities in the center of the city، and wide area of worn- out textures. Parking deficiency is one of the difficulties of this city which is dealt with in this research. The aim of this article is evaluating the need for parking in Kerman city. The research method is qualitative and analytical type. Different methods of mathematics and statistics were applied such as the conventional weight model، AHP، Topsis and Fuzzy approaches along with the detection of those areas of the City which held the higher demand for parking spaces in Kerman. The attempt was to discover the preferable model for the detection of these areas. In order to obtain Zoning Maps of the layers of information on the distance from the mal، the concentration of commercial centers، health care centers، and administrative centers، the population، the distance from the high way، the distance from boulevard، and street، also the distance from the colleges and universities (educational centers in the city)، from the cultural centers، and parking spaces were taken into consideration. To evaluate the models، the relevant layers of the available public parking and the location of the mal was considered. Final results revealed that most of the areas which highly require parking spaces are located in the center of the city and the conventional weight model best demonstrated this demand than other models and AHP and TOPSIS، Fuzzy show the high need to parking at a lower level.