Travel Behavior Analysis of Event-Related Urban Rail Transit Passengers during Large Special Events

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Travel Behavior Analysis of Event-Related Urban Rail Transit Passengers during Large Special Events

Wang, Xingchuan / Yao, Enjian

Large special events always generate additional traffic demands (i.e., event-related passengers), which usually stresses the urban rail transit with a much more severe test than normal conditions. In order to provide better operational measures and guarantee traffic security during the event, it is important to identify the impact and evaluate the influence of the event-related passengers (ERPs). Considering the China import and export fair (Canton Fair) as an example, this paper proposes a data mining method to identify the influenced stations and estimate the event-related passenger flow using data gathered by the automated fare collection (AFC) system of Guangzhou Metro. Meanwhile, based on the analysis of land-use and other attributes of urban rail transit stations, a multinomial logit (MNL) based destination choice model is introduced to account for the ERPs’ travel behaviors. The result shows that station attributes (e.g., attraction of the stations, land use type, land use intensity) and some level of service variables (such as travel time, transfer time, and station betweenness calculated by network analysis) play an important role in the destination choice behavior of the ERPs. Thus, the model is capable of accurately describing the ERPs’ choice behavior during large special event. The study is helpful to accurately estimate the passengers’ destination choice behavior and make reasonable operational plans during large special events for urban rail transit operator.