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http://dx.doi.org/10.12652/Ksce.2017.37.3.0593

Development of Parking Space Forecast Model for Large Traffic-inducing Facilities Considering Surrounding Circumstance  

Park, Je jin (Korea Expressway Corporation)
Oh, Seok Jin (Chonnam National University)
Kim, Sung Hun (Chonnam National University)
Ha, Tae Jun (Chonnam National University)
Publication Information
KSCE Journal of Civil and Environmental Engineering Research / v.37, no.3, 2017 , pp. 593-601 More about this Journal
Abstract
With the rapid industrial development and national economic advance since 1970, the national income of Korea has sharply increased. As a result, issues regarding city expansion, urban concentration, increase in the number of registered motor vehicles, and increase in traffic have caused transportation issues such as traffic congestion and problems with parking. Especially, enforcement ordinances and rules have been established on installation and management of parking lots to solve problems with parking which are raised as social problems such as conflict with neighbors but the flexible calculation of legal parking space has the limitations because of the diversity and complex functionality of purposes of facilities. Accordingly, this study attempted to supplement such demerit of the parking space demand forecast method based on the legally required number of parking spaces and average unit requirement in the parking space supply. This study estimated the required number of parking spaces by analyzing existing literature, collecting field research data, and analyzing the factors that have an impact on the parking demand. Also, it compared the required number of parking spaces based on the average unit requirement as well as the required number of parking spaces by the forecast model based on the cumulative number of motor vehicles parked. The result was that the required number of parking space based on average unit requirement was less than the cumulative number of motor vehicles parked by 9.99%. Meanwhile, the required number of parking spaces by the forecast model was more than the cumulative number of motor vehicles parked by 4.37%. Therefore, it is believed that the parking space forecast model is more efficient than the others in estimating there quired parking space. The parking space forecast model of this study consider different environmental factors to enable practical parking demand forecast considering the local characteristics and thus supply the parking space in an efficient way.
Keywords
Transportation impact facility; Parking space; Average parking unite; Multiple regresiion;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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