Spatial variations in urban public ridership derived from GPS trajectories and smart card data

Authors

Wei Tu
Rui Cao
Yang Yue
Baoding Zhou
Qiuping Li
Qingquan Li

Document Type

Journal Article

Publication Date

2018

Subject Area

place - asia, place - urban, mode - taxi, mode - subway/metro, mode - bus, technology - passenger information, technology - geographic information systems, ridership - mode choice

Keywords

Ridership, Big data, Trajectory, Smart card data, Geographically weighted regression, Transit, Taxi

Abstract

Understanding urban public ridership is essential for promoting public transportation. However, limited efforts have been made to reveal the spatial variations of multi-modal public ridership (such as buses, metro systems, and taxis) and the underlying controlling factors. This study explores multi-modal public ridership and compares the similarities and differences of the associated factors. Daily bus, metro, and taxi ridership patterns are first extracted from multiple sources of big transportation data, including vehicle (bus and taxi) GPS trajectories and smart card data. Multivariate regression analysis and geographically weighted regression analysis are used to reveal the associations between these data and demographic, land use, and transportation factors. An empirical study in Shenzhen, China, suggests that employment, mixed land use, and road density have significant effects on the ridership of each mode; however, some effects vary from negative to positive across the city. The results also indicate that road density, income, and metro accessibility do not have significant effects on metro, transit or bus ridership. These findings suggest that the effects of the associated factors vary depending on the mode of travel being considered and that the city should carefully consider which factors to emphasize in formulating future transport policy.

Rights

Permission to publish the abstract has been given by Elsevier, copyright remains with them.

Comments

Journal of Transport Geography home Page:

http://www.sciencedirect.com/science/journal/09666923

Recommended Citation

Tu, W., Cao, R., Yue, Y., Zhou, B., Li, Q., & Li, Q. (2018). Spatial variations in urban public ridership derived from GPS trajectories and smart card data. Journal of Transport Geography, Vol. 69, pp. 45-57.