Modelling the urban rail ridership in Kuala Lumpur by pedestrian infrastructure designs, land use and station characteristics
Urban rail transit, however, must run at the ideal volume of passenger ridership. Otherwise, it is not feasible. It means the geographical location of urban rail stations has to be appropriate. However, what is the elements to consider for the location of the urban rail station? The literature claim...
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Main Authors: | , , , |
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Format: | Conference or Workshop Item |
Language: | English English |
Published: |
2021
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Online Access: | http://irep.iium.edu.my/92731/1/92731_Modelling%20the%20urban%20rail%20ridership%20in%20Kuala%20Lumpur.pdf http://irep.iium.edu.my/92731/2/92731_Modelling%20the%20urban%20rail%20ridership%20in%20Kuala%20Lumpur_schedule.pdf http://irep.iium.edu.my/92731/ https://easts.hiroshima-u.ac.jp/programme/ |
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Institution: | Universiti Islam Antarabangsa Malaysia |
Language: | English English |
Summary: | Urban rail transit, however, must run at the ideal volume of passenger ridership. Otherwise, it is not feasible. It means the geographical location of urban rail stations has to be appropriate. However, what is the elements to consider for the location of the urban rail station? The literature claimed land use characteristics such as land use density, land use diversity, and land use types; residential, commercial, and institutional affect urban rail ridership. Moreover, land use characteristics and urban rail ridership assisted by pedestrian infrastructures designs can increase urban rail ridership. Thus, this paper is to study the effect of land use and station characteristics as well as pedestrian infrastructures designs on urban rail ridership in Kuala Lumpur. Kelana Jaya line and Ampang line are two selected LRT lines for the study. There are four data sets: land use characteristics, pedestrian infrastructure designs, station characteristics, and passenger ridership. Three regression models were produced in predicting the Kelana Jaya line and Ampang line separately as well as the combined model. |
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