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Author:

Lin, Pengfei (Lin, Pengfei.) | Weng, Jiancheng (Weng, Jiancheng.) | Yin, Baocai (Yin, Baocai.) (Scholars:尹宝才) | Zhou, Xiang (Zhou, Xiang.)

Indexed by:

CPCI-S

Abstract:

Urban traffic congestion has become a big problem that obstructs sustainable urban development. Enhancing the road network operation quality is an effective way to alleviate congestion. The evaluation of urban road network operation quality is different from the congestion evaluation; it is a method for measuring the controllability of urban road network with increasing traffic demand pressure. Based on the two-fluid model of urban macroscopic traffic flow theory, two indicators including the Traffic Smoothness Index (TSI) and the Network Adaptability Index (NAI) were established to describe the urban road network operation quality. The model of large-scale high-frequency trajectory data processing to calculate the operation quality evaluation indicators was proposed. Then, two China cities of Beijing and Shanghai were taken as examples to analyze the operation quality of urban road network The results show that the quality of the road network operation in Shanghai is better than that of Beijing. The degree of smoothness of the two cities' road network gradually improves from the downtown area to the border of urban area, but the road network in downtown areas have higher adaptability in both cities. The study is of great significance to improve the operation quality of urban road network and the service level of traffic system.

Keyword:

Urban Road Network Operation Quality High-frequency Trajectory Data Two-fluid Model

Author Community:

  • [ 1 ] [Lin, Pengfei]Beijing Univ Technol, Beijing Key Lab Traff Engn, Beijing, Peoples R China
  • [ 2 ] [Weng, Jiancheng]Beijing Univ Technol, Beijing Key Lab Traff Engn, Beijing, Peoples R China
  • [ 3 ] [Yin, Baocai]Beijing Univ Technol, Beijing Key Lab Traff Engn, Beijing, Peoples R China
  • [ 4 ] [Zhou, Xiang]Chinese Acad Sci, Inst Remote Sensing Applicat, Beijing, Peoples R China

Reprint Author's Address:

  • [Lin, Pengfei]Beijing Univ Technol, Beijing Key Lab Traff Engn, Beijing, Peoples R China

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Source :

2018 21ST INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC)

ISSN: 2153-0009

Year: 2018

Page: 3602-3607

Language: English

Cited Count:

WoS CC Cited Count: 2

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 6

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