Predication of the Urban Rail Transit Commuter Flows in Long Trip Chains

Urban rail transit is a type of high-capacity public transport with high speed, and thus, it is an optimal and popular travel mode for commuters. A trip chain of a commuter from origin to destination might contain not only urban rail transit. This study aims to investigate the relationship between urban rail transit and other travel mode, and then, predict the urban rail transit commuter flows based on these trip chains. More specifically, this paper firstly defined a commuter trip chain containing urban rail transit and reviewed the existing prediction methods. Secondly, the model of urban rail transit commuters was established based on a two-layer Nested Logit model. Furthermore, this study used the data collected at the Xiaolingwei Station of Nanjing subway as a case study. The results partially validated the performance of the proposed model, which could be an assistant to plan the transfer facilities of an urban rail transit station for commuters transferring from/to rail transit.