Abstract
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.
Highlights
The urban rail transit system is in the stage of network operation in megacities in China including Beijing, Shanghai, Guangzhou and Shenzhen
To fill the important knowledge gaps, this study investigates the extraction of transfer passenger flow based on the transfer choice behaviours of passengers and the influencing factors for transfer passenger flow
Where r p,r is the cumulative number of transfers at the transfer station p of route r between the OD, and β is the parameter to be calibrated, which can be obtained via surveys; it is a penalty factor for the number of passenger transfers to reflect the increase in cost of the transfer, so the range of values is set from 1 to 2
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Urban rail transit in China primarily adopts an operation mode of integrated ticketing, and passenger travel intermediate information, such as transfer and route selection, cannot be calculated due to the difficulty of collection via AFC systems. Numerous studies of the calculation of passenger flow assignment with respect to urban rail transit have been conducted. Si et al [9] considered influencing factors, including total travel time and transfer cost, in a logit-based passenger flow assignment model. Zhou and Xu [10] devised a passenger flow assignment model for urban rail transit based on the entry and exit time and the train operation constraints. Numerous studies on the relationship between urban rail transit ridership and influencing factors have been conducted [13,14,15].
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