Analyzing Influencing Factors of Transfer Passenger Flow of Urban Rail Transit: A New Approach Based on Nested Logit Model Considering Transfer Choices
With the continuous improvement of the operation line network of urban rail transit, analyzing influencing factors of transfer passenger flow of urban rail transit is critical to improve the transfer demand analysis of urban rail transit. Using data collected from questionnaires, transfer passenger...
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doaj-a1311d1304b4423f84d11f51e266b7022021-08-26T13:49:09ZengMDPI AGInternational Journal of Environmental Research and Public Health1661-78271660-46012021-08-01188462846210.3390/ijerph18168462Analyzing Influencing Factors of Transfer Passenger Flow of Urban Rail Transit: A New Approach Based on Nested Logit Model Considering Transfer ChoicesZhenjun Zhu0Jun Zeng1Xiaolin Gong2Yudong He3Shucheng Qiu4College of Automobile and Traffic Engineering, Nanjing Forestry University, No.159 Longpan Road, Nanjing 210037, ChinaSchool of Transportation, Southeast University, No.2 Dongnandaxue Road, Nanjing 211189, ChinaCollege of Automobile and Traffic Engineering, Nanjing Forestry University, No.159 Longpan Road, Nanjing 210037, ChinaCollege of Automobile and Traffic Engineering, Nanjing Forestry University, No.159 Longpan Road, Nanjing 210037, ChinaCollege of Automobile and Traffic Engineering, Nanjing Forestry University, No.159 Longpan Road, Nanjing 210037, ChinaWith the continuous improvement of the operation line network of urban rail transit, analyzing influencing factors of transfer passenger flow of urban rail transit is critical to improve the transfer demand analysis of urban rail transit. Using data collected from questionnaires, transfer passenger flow surveys and smart cards, this study proposes an approach base on nested logit passenger flow assignment model considering transfer choice behaviours of passengers. The transfer passenger flow at seven transfer stations in Nanjing is obtained. Subsequently, this study investigates the potential influencing factors of transfer passenger flow, including the node degree, geographic location (located in the city center, urban fringe, suburbs or suburban fringe), economic location (distance from the city center) and transportation locations (if it is close to a transportation hub or in combination with the hub) of rail transit transfer stations. The results indicate that a positive correlation between the transfer passenger flow and the node degrees of transfer stations. However, the relationship between transfer passenger flow and the economic, geographic, and transportation locations of transfer stations is not clear. The finding have reference value for the network design of rail transit transfer stations and transfer facilities, and provide reference for the analysis of passenger flow under network operation.https://www.mdpi.com/1660-4601/18/16/8462transfer passenger flowurban rail transittransfer choicenested logit modelNanjing |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Zhenjun Zhu Jun Zeng Xiaolin Gong Yudong He Shucheng Qiu |
spellingShingle |
Zhenjun Zhu Jun Zeng Xiaolin Gong Yudong He Shucheng Qiu Analyzing Influencing Factors of Transfer Passenger Flow of Urban Rail Transit: A New Approach Based on Nested Logit Model Considering Transfer Choices International Journal of Environmental Research and Public Health transfer passenger flow urban rail transit transfer choice nested logit model Nanjing |
author_facet |
Zhenjun Zhu Jun Zeng Xiaolin Gong Yudong He Shucheng Qiu |
author_sort |
Zhenjun Zhu |
title |
Analyzing Influencing Factors of Transfer Passenger Flow of Urban Rail Transit: A New Approach Based on Nested Logit Model Considering Transfer Choices |
title_short |
Analyzing Influencing Factors of Transfer Passenger Flow of Urban Rail Transit: A New Approach Based on Nested Logit Model Considering Transfer Choices |
title_full |
Analyzing Influencing Factors of Transfer Passenger Flow of Urban Rail Transit: A New Approach Based on Nested Logit Model Considering Transfer Choices |
title_fullStr |
Analyzing Influencing Factors of Transfer Passenger Flow of Urban Rail Transit: A New Approach Based on Nested Logit Model Considering Transfer Choices |
title_full_unstemmed |
Analyzing Influencing Factors of Transfer Passenger Flow of Urban Rail Transit: A New Approach Based on Nested Logit Model Considering Transfer Choices |
title_sort |
analyzing influencing factors of transfer passenger flow of urban rail transit: a new approach based on nested logit model considering transfer choices |
publisher |
MDPI AG |
series |
International Journal of Environmental Research and Public Health |
issn |
1661-7827 1660-4601 |
publishDate |
2021-08-01 |
description |
With the continuous improvement of the operation line network of urban rail transit, analyzing influencing factors of transfer passenger flow of urban rail transit is critical to improve the transfer demand analysis of urban rail transit. Using data collected from questionnaires, transfer passenger flow surveys and smart cards, this study proposes an approach base on nested logit passenger flow assignment model considering transfer choice behaviours of passengers. The transfer passenger flow at seven transfer stations in Nanjing is obtained. Subsequently, this study investigates the potential influencing factors of transfer passenger flow, including the node degree, geographic location (located in the city center, urban fringe, suburbs or suburban fringe), economic location (distance from the city center) and transportation locations (if it is close to a transportation hub or in combination with the hub) of rail transit transfer stations. The results indicate that a positive correlation between the transfer passenger flow and the node degrees of transfer stations. However, the relationship between transfer passenger flow and the economic, geographic, and transportation locations of transfer stations is not clear. The finding have reference value for the network design of rail transit transfer stations and transfer facilities, and provide reference for the analysis of passenger flow under network operation. |
topic |
transfer passenger flow urban rail transit transfer choice nested logit model Nanjing |
url |
https://www.mdpi.com/1660-4601/18/16/8462 |
work_keys_str_mv |
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