A Two-Step Model for Predicting Travel Demand in Expanding Subways

Kaipeng Wang; Pu Wang; Zhiren Huang; Ximan Ling; Fan Zhang; Anthony Chen

doi:10.1109/TITS.2022.3166669

A Two-Step Model for Predicting Travel Demand in Expanding Subways

Kaipeng Wang, Pu Wang, Zhiren Huang, Ximan Ling, Fan Zhang, Anthony Chen

Research output: Journal article publication › Journal article › Academic research › peer-review

3 Citations (Scopus)

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
Pages (from-to)	19534-19543
Number of pages	10
Journal	IEEE Transactions on Intelligent Transportation Systems
Volume	23
Issue number	10
DOIs	https://doi.org/10.1109/TITS.2022.3166669
Publication status	Published - 1 Oct 2022

Keywords

Subway
line extension
new lines
travel demand prediction

ASJC Scopus subject areas

Automotive Engineering
Mechanical Engineering
Computer Science Applications

More information

10.1109/TITS.2022.3166669

Cite this

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title = "A Two-Step Model for Predicting Travel Demand in Expanding Subways",

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.",

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author = "Kaipeng Wang and Pu Wang and Zhiren Huang and Ximan Ling and Fan Zhang and Anthony Chen",

note = "Funding Information: This work was supported in part by the National Natural Science Foundation of China under Grant 71871224; in part by the Science and Technology Progress and Innovation Plan of Department of Transportation of Hunan Province under Grant 212102; in part by the Research Grants Council of the Hong Kong Special Administrative Region through The Hong Kong Polytechnic University (PolyU) under Grant 15212217; in part by the Research Committee of The Hong Kong Polytechnic University under Grant 1-ZVJV; and in part by the Hong Kong Branch of National Rail Transit Electrification and Automation Engineering Technology Research Center, The Hong Kong Polytechnic University, under Grant K-BBY1. Publisher Copyright: {\textcopyright} 2000-2011 IEEE.",

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AU - Huang, Zhiren

AU - Ling, Ximan

AU - Zhang, Fan

AU - Chen, Anthony

N1 - Funding Information: This work was supported in part by the National Natural Science Foundation of China under Grant 71871224; in part by the Science and Technology Progress and Innovation Plan of Department of Transportation of Hunan Province under Grant 212102; in part by the Research Grants Council of the Hong Kong Special Administrative Region through The Hong Kong Polytechnic University (PolyU) under Grant 15212217; in part by the Research Committee of The Hong Kong Polytechnic University under Grant 1-ZVJV; and in part by the Hong Kong Branch of National Rail Transit Electrification and Automation Engineering Technology Research Center, The Hong Kong Polytechnic University, under Grant K-BBY1. Publisher Copyright: © 2000-2011 IEEE.

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N2 - 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.

AB - 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.

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KW - line extension

KW - new lines

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A Two-Step Model for Predicting Travel Demand in Expanding Subways

Abstract

Keywords

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