| Title |
Development of Parking Space Forecast Model for Large Traffic-inducing Facilities Considering Surrounding Circumstance |
| Authors |
박제진(Park, Je jin) ; 오석진(Oh, Seok Jin) ; 김성훈(Kim, Sung Hun) ; 하태준(Ha, Tae Jun) |
| DOI |
https://doi.org/10.12652/Ksce.2017.37.3.0593 |
| Keywords |
교통유발시설;주차면;평균주차원단위;다중회귀 Transportation impact facility;Parking space;Average parking unite;Multiple regresiion |
| 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. |