Revealing the determinants of the intermodal transfer ratio between metro and bus systems considering spatial variations
Journal article, 2022

Buses and metros are two main public transit modes, and these modes are crucial components of sustainable transportation systems. Promoting reciprocal integration between bus and metro systems requires a deep understanding of the effects of multiple factors on transfers among integrated public transportation transfer modes, i.e., metro-to-bus and bus-to-metro. This study aims to reveal the determinants of the transfer ratio between bus and metro systems and quantify the associated impacts. The transfer ratio between buses and metros is identified based on large-scale transaction data from automated fare collection systems. Meanwhile, various influencing factors, including weather, socioeconomic, the intensity of business activities, and built environment factors, are obtained from multivariate sources. A multivariate regression model is used to investigate the associations between the transfer ratio and multiple factors. The results show that the transfer ratio of the two modes significantly increases under high temperature, strong wind, rainfall, and low visibility. The morning peak hours attract a transfer ratio of up to 57.95%, and the average hourly transfer volume is 0.94 to 1.38 times higher at this time than in other periods. The intensity of business activities has the most significant impact on the transfer ratio, which is approximately 1.5 to 15 times that of the other independent variables. Moreover, an adaptative geographically weighted regression is utilized to investigate the spatial divergences of the influences of critical factors on the transfer ratio. The results indicate that the impact of a factor presents spatial heterogeneity and even shows opposite effects (in terms of positive and negative) on the transfer ratio in different urban contexts. For example, among the related socioeconomic variables, the impact of the housing price on the downtown transfer ratio is larger than that in the suburbs. Crowd density positively influences the transfer ratio at most stations in the northern region, whereas it shows negative results in the southern region. These findings provide valuable insights for public transportation management and promote the effective integration of bus and metro systems to provide enhanced transfer services.

Transfer ratio

Geographically weighted regression

Public transit

Multiple weather effects

Smartcard data

Spatial variations

Author

Pan Wu

South China University of Technology

Lunhui Xu

South China University of Technology

Lingshu Zhong

Chalmers, Architecture and Civil Engineering, Geology and Geotechnics

Kun Gao

Transportgruppen

Xiaobo Qu

Tsinghua University

Mingyang Pei

South China University of Technology

Journal of Transport Geography

0966-6923 (ISSN)

Vol. 104 103415

Subject Categories

Transport Systems and Logistics

Environmental Analysis and Construction Information Technology

DOI

10.1016/j.jtrangeo.2022.103415

More information

Latest update

9/1/2022 1