• Title/Summary/Keyword: Walk Access Ridership

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Estimating Walk Access and Auto Access Ridership for Transit Demand Forecast (대중교통수요예측을 위한 보행접근 및 승용차접근 잠재수요의 추정)

  • Yun, Seong-Soon;Yun, Dae-Sic
    • Journal of Korean Society of Transportation
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    • v.21 no.6
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    • pp.43-55
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    • 2003
  • This paper presents a new method for estimating potential transit ridership residential population and number of employees that have accesses to transit services. A standard procedure that can be used to determine transit accessibility by pedestrians ad automobiles are developed to improve its transit demand forecasting capability. The analysis results are compared with those from the traditional buffer method as well as the network ratio method. It was found that the proposed method is more accurate than the traditional methods. The new method can be used to better estimate the "Walk Access" transit trips and "Auto Access" transit trips in the Mode Choice Model.

Analysis of Public Transport Ridership during a Heavy Snowfall in Seoul (기상상황에 따른 서울시 대중교통 이용 변화 분석: 폭설을 중심으로)

  • Won, Minsu;Cheon, Seunghoon;Shin, Seongil;Lee, Seonyeong
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.39 no.6
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    • pp.859-867
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    • 2019
  • Severe weather conditions, such as heavy snowfall, rain, heatwave, etc., may affect travel behaviors of people and finally change traffic patterns in transportation networks. To deal with those changes and prevent any negative impacts on the transportation system, understanding those impacts of severe weather conditions on the travel patterns is one of the critical issues in the transportation fields. Hence, this study has focused on the impacts of a weather condition on travel patterns of public transportations, especially when a heavy snowfall which is one of the most critical weather conditions. First, this study has figured out the most significant weather condition affecting changes of public transport ridership using weather information, card data for public transportation, mobile phone data; and then, developed a decision-tree model to determine complex inter-relations between various factors such as socio-economic indicators, transportation-related information, etc. As a result, the trip generation of public transportations in Seoul during a heavy snowfall is mostly related to average access times to subway stations by walk and the number of available parking lots and spaces. Meanwhile, the trip attraction is more related to business and employment densities in that destination.