碩士 / 淡江大學 / 運輸管理學系碩士班 / 104 / In recent years central and local governments have deployed public transportation systems; however, the growth rate of public transportation usage is still below the expected level. According to results of Ministry of Transportation and Statistics Department the proportion of public transportation usage has grown in recent three years but the scale of growth proportion decreases annually. It shows that a gap exists between public transportation service supply and travel demand. Therefore, most of people still rely on private transportation instead of public transportation.
In order to understand characteristics of public transportation service and to construct relevance models of travel pattern according to time and space for public transportation commuters, this study will focus on analyzing big data of Easycard and clustering commuters by using trip length and trip time. Furthermore, a questionnaires survey is also conducted to explore travel patterns and service gap cognition of commuters in a real case.
Results show that most of commuters really travel according to trip time and trip length. It is also shown that commuters will take bus when their trip lengths are between 1 and 5 kilometers, while take MRT when their trip lengths are over 15 kilometers. The results of the questionnaires survey shows three incentive scenarios of concessionary fare, the maximum frequency of taking public transportation and the mileage calculation can effectively change usage frequencies of motorcyclists. Using the scenario of concessionary fare it will attract commuters who drive motorcycle once or twice every week or take public transportations once to twice every week. In the scenario of the maximum frequency of taking public transportation, it will attract commuters who drive motorcycle every week with income per month below 10,000 NTD. While in the scenario of mileage calculation it will attract commuters who take public transportation once or twice every week with income per month below 10,000 NTD and average travel time between 40 to 50 minutes.
In summary, this study constructs travel patterns of public transportation commuters by using big data from Easycard database. It is suggested to explore more detailed travel behavior relevance models in future.
| Identifer | oai:union.ndltd.org:TW/104TKU05425006 |
| Date | January 2016 |
| Creators | Hao-Wei Lin, 林浩瑋 |
| Contributors | 陶治中 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | zh-TW |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 105 |
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