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Author:

Long, Xue-Qin (Long, Xue-Qin.) | Guan, Hong-Zhi (Guan, Hong-Zhi.) (Scholars:关宏志) | Zhao, Xin (Zhao, Xin.) | Qin, Huan-Mei (Qin, Huan-Mei.)

Indexed by:

EI Scopus PKU CSCD

Abstract:

In order to study the trip distribution between traffic zones according to the trip behaviors of the residents, forecast method for trip distribution was proposed based on trip chains, with the relationships among land use patterns, residents' activities and urban transport considered. First, the model for the relationship between trip generation and land use patterns and population was established. Then the trip chain types were divided into 8 according to the trip purposes and sequences. After the trip chain was decomposed into different activities, according to the purpose and attraction of each pattern of land use in each trip, the trip distribution between two zones in a trip chain was determined. When all zones and trip chains were considered, trip distributions of all traffic zones were determined. At last, the results of the study were verified by an example. The results show that the average error between the forecast results and the actual data is 8.4%, which means the method is effective.

Keyword:

Motor transportation Forecasting Urban transportation Zoning Highway engineering Traffic control Land use

Author Community:

  • [ 1 ] [Long, Xue-Qin]Beijing Key Lab. of Transportation of Engineering, Beijing University of Technology, Beijing 100124, China
  • [ 2 ] [Long, Xue-Qin]School of Highway, Chang'an University, Xi'an 710064, Shaanxi, China
  • [ 3 ] [Guan, Hong-Zhi]Beijing Key Lab. of Transportation of Engineering, Beijing University of Technology, Beijing 100124, China
  • [ 4 ] [Zhao, Xin]Beijing Key Lab. of Transportation of Engineering, Beijing University of Technology, Beijing 100124, China
  • [ 5 ] [Qin, Huan-Mei]Beijing Key Lab. of Transportation of Engineering, Beijing University of Technology, Beijing 100124, China

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Source :

China Journal of Highway and Transport

ISSN: 1001-7372

Year: 2014

Issue: 1

Volume: 27

Page: 107-112

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: 13

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