01697557

Component

Promoting the ratio of rail transit in urban travel demand is an important way to develop sustainable mobility. Deep understanding the intrinsic structure of the taxi demand is a critical way to expose the potential users of the public transit and enhance its service quality. This paper proposes a novel method to mine the potential rail transit demand from taxi trajectory data considering the space and time constraints simultaneously. This demand refers to the taxi trip which probably shifts from taxi mode to rail transit if the service is improved. A huge set of the taxi trajectory data was collected in Shanghai, China. Several data mining techniques were applied in regional demand estimation and its decomposition to different modes, such like the matrix decomposition and clustering approaches. The results show that the proposed methods effectively extracted the potential access/egress travel demand of rail transit and its spatiotemporal distribution patterns were significantly different among different metro stations. This study could improve our understanding of the generation pattern of potential demand using public transit service. Such information is useful for developing the policy to encourage mode shift and increase transit ridership.

This paper was sponsored by TRB committee AP000 Public Transportation Group.

19-04598

English

0000-0002-7580-3559

6p

2019

Transportation Research Board 98th Annual Meeting

Digital/other

Figures; Maps

Data mining; Global Positioning System; Rail transit; Suburbs; Taxi services; Travel demand

Shanghai (China)

Data and Information Technology; Planning and Forecasting; Railroads

Transportation Research Board Annual Meeting 2019 Paper #19-04598

TRIS, TRB, ATRI

Dec 7 2018 9:31AM