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                      Study on Parking Demand and Verification for Residential Land Use in Downtown Area of Yangon
                                                                 Nann Yu Lwin#1, Khin Latt#2
                               #Department of Civil Engineering, West Yangon Technological University
                                                    Yangon, Republic of the Union of Myanmar
                                                                      [email protected]
ABSTRACT
This study aims to characterize the current parking conditions of the selected downtown areas of Yangon. The objective of this study is to provide the parking demand model for Latha township and to verify the resulting model with the data from Paedan township. The two selected townships are generally equal in household size. Firstly, the data collection was conducted and then analyzed the parking demand model by using multiple linear regression method. The collected data included peak parking demand received by making field survey in the early morning before making the trip and the questionnaire surveyed to the home of the sample respondents on the selected study areas. The results from parking demand model was mainly influenced by three independent variables which are the total number of household in ward, the total number of vehicle owned for sample respondents and the average walking distance to the destination. The regression equation established for this study found to have a high degree of coefficient of variation, R2 = 0.908 for this independent variables. When the obtained model was verified with the parking data from Pabedan township, the results are met to the actual parking demand. This information could help the planners to implement the appropriate parking supply for the similar household size. Finally, this study is recommended that in order to reduce traffic congestion, delays on study area, on-street parking and adequate off-street parking facilities should be provided.
Keywords— Latha township, Parking condition, Multiple linear regression, Parking demand, Coefficient of variation