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Author:

Wang, Shu-Wei (Wang, Shu-Wei.) | Sun, Li-Shan (Sun, Li-Shan.) (Scholars:孙立山) | Hao, Si-Yuan (Hao, Si-Yuan.) | Rong, Jian (Rong, Jian.) (Scholars:荣建)

Indexed by:

EI Scopus CSCD

Abstract:

The existing transit ridership models describe land use with indexes such as population, employment and land use area, these indexes can't describe the diversity and complexity of land use development, thus make it difficult to reveal the influence mechanism of mixed land use on travel demand. This paper quantifies the precise land use characteristics of Beijing transit station catchment areas using POIs (points of interest) extract from an electronic map. Through the regression analysis of precise land use and transit station boarding volume, a direct ridership model is built based on the influence mechanism analysis of land use, traffic and location factors on transit ridership. Following validation shows the prediction accuracy of the proposed model meets expectation, reveals the strong correlation between land use and transit ridership. ©, 2015 All right reserved.

Keyword:

Catchments Motor transportation Regression analysis Land use

Author Community:

  • [ 1 ] [Wang, Shu-Wei]Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Wang, Shu-Wei]Institute of Comprehensive Transportation of National Development and Reform Commission, Beijing; 100038, China
  • [ 3 ] [Sun, Li-Shan]Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing; 100124, China
  • [ 4 ] [Hao, Si-Yuan]Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing; 100124, China
  • [ 5 ] [Rong, Jian]Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing; 100124, China

Reprint Author's Address:

  • 孙立山

    [sun, li-shan]beijing key laboratory of traffic engineering, beijing university of technology, beijing; 100124, china

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Source :

Journal of Transportation Systems Engineering and Information Technology

ISSN: 1009-6744

Year: 2015

Issue: 3

Volume: 15

Page: 37-43

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 26

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