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Author:

Qin, Huan-Mei (Qin, Huan-Mei.) | Guan, Hong-Zhi (Guan, Hong-Zhi.) (Scholars:关宏志) | Pan, Xiao-Song (Pan, Xiao-Song.)

Indexed by:

EI Scopus PKU CSCD

Abstract:

It was assumed that the travel demand density is uniformly distributed along the corridor in a monocentric city with railway and main roads and the railway has the continuously distributed stations to analyze the traveller park and ride demand distribution characteristics. A hierarchical disaggregated model was proposed considering the traffic mode choice including the car, the railway, the park and ride, and the parking lot. By the method of stochastic continuum equilibrium model in combination with numerical examples, it was found that the park and ride demand appears highest at a certain distance range and decreases with the increase of the transfer time. The park and ride lots attract some, although relatively small backward ride demand. Large park and ride demand comes from the peripheral of the city and the demand intensity decreases with the increase of the distance to the lots. When the parking lot capacity is restricted, the park and ride traveller may change the transfer lot. These results provide a reference for the planning and construction of the park and ride facilities.

Keyword:

Stochastic models Numerical methods Site selection Railroads Stochastic systems

Author Community:

  • [ 1 ] [Qin, Huan-Mei]Beijing Key Lab of Traffic Engineering, Beijing University of Technology, Beijing 100124, China
  • [ 2 ] [Guan, Hong-Zhi]Beijing Key Lab of Traffic Engineering, Beijing University of Technology, Beijing 100124, China
  • [ 3 ] [Pan, Xiao-Song]Beijing Key Lab of Traffic Engineering, Beijing University of Technology, Beijing 100124, China

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Source :

Journal of Jilin University (Engineering and Technology Edition)

ISSN: 1671-5497

Year: 2012

Issue: 2

Volume: 42

Page: 321-326

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: 2

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