Abstract
In many cities, subways are expanding with new or extended lines being built and put into operations. The prediction of future travel demand in subway with the planned expansion is of significant importance because such information is crucial for new line planning and new network operations. In this study, we identify the determinant features from potential influential factors of passenger travel demand and develop a two-step model for predicting passenger travel demand in expanding subways. The proposed model is tested in an actual subway with a new line being put into operations, and achieves higher prediction accuracy than the benchmark models.
Original language | English |
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Journal | IEEE Transactions on Intelligent Transportation Systems |
DOIs | |
Publication status | Accepted/In press - 2022 |
Keywords
- Data models
- line extension.
- new lines
- Predictive models
- Public transportation
- Rails
- Sociology
- Statistics
- Subway
- travel demand prediction
- Urban areas
ASJC Scopus subject areas
- Automotive Engineering
- Mechanical Engineering
- Computer Science Applications