Enhancing MRT purple line offset project through forecasting ridership using the direct demand ridership model

The Mass Rapid Transit (MRT) Purple Line project is part of the Thai government’s energy- and transportation-related greenhouse gas reduction plan. The number of passengers estimated during the feasibility study period was used to calculate the greenhouse gas reduction effect of project implementation. Most of the estimated numbers exceed the actual number of passengers, resulting in errors in estimating greenhouse gas emissions. This study employed a direct demand ridership model (DDRM) to accurately predict MRT Purple Line ridership. The variables affecting the number of passengers were the population in the vicinity of stations, offices, and shopping malls, the number of bus lines that serve the area, and the length of the road. The DDRM accurately predicted the number of passengers within 10% of the observed change and, therefore, the project can help reduce greenhouse gas emissions by 1289 tCO2 in 2023 and 2059 tCO2 in 2030.

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Publication Details

Journal
Journal of Infrastructure Policy and Development
Published
2025-03-04
DOI
https://doi.org/10.24294/jipd6564
Primary Topic
Transportation and Mobility Innovations
Type
article
Field-Weighted Citation Impact
0.00
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article

Enhancing MRT purple line offset project through forecasting ridership using the direct demand ridership model

Hyemin Park, Dezhen Yang, Kamonchanok Wangvittaya
Journal of Infrastructure Policy and Development
Transportation and Mobility Innovations
article

Enhancing MRT purple line offset project through forecasting ridership using the direct demand ridership model

Hyemin Park, Dezhen Yang, Kamonchanok Wangvittaya
article en

Abstract

The Mass Rapid Transit (MRT) Purple Line project is part of the Thai government’s energy- and transportation-related greenhouse gas reduction plan. The number of passengers estimated during the feasibility study period was used to calculate the greenhouse gas reduction effect of project implementation. Most of the estimated numbers exceed the actual number of passengers, resulting in errors in estimating greenhouse gas emissions. This study employed a direct demand ridership model (DDRM) to accurately predict MRT Purple Line ridership. The variables affecting the number of passengers were the population in the vicinity of stations, offices, and shopping malls, the number of bus lines that serve the area, and the length of the road. The DDRM accurately predicted the number of passengers within 10% of the observed change and, therefore, the project can help reduce greenhouse gas emissions by 1289 tCO2 in 2023 and 2059 tCO2 in 2030.

Journal of Infrastructure Policy and DevelopmentVol. 9(2)
University of Seoul (KR)
Openalex Percentile: Top 97%
Transportation and Mobility Innovations
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