| Title |
Analysis of Public Transport Ridership during a Heavy Snowfall in Seoul |
| Authors |
원민수(Won, Minsu) ; 천승훈(Cheon, Seunghoon) ; 신성일(Shin, Seongil) ; 이선영(Lee, Seonyeong) |
| DOI |
https://doi.org/10.12652/Ksce.2019.39.6.0859 |
| Keywords |
기상;대중교통수요;통신데이터;카드데이터;의사결정모델 Weather condition;Public transport ridership;Card data;Mobile phone data;Decision-tree model |
| Abstract |
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. |