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Author:

Hu, Jiang-Bi (Hu, Jiang-Bi.) (Scholars:胡江碧) | Fei, Xue-Liang (Fei, Xue-Liang.) | Liu, Xiao-Ming (Liu, Xiao-Ming.) (Scholars:刘小明)

Indexed by:

EI Scopus PKU CSCD

Abstract:

It's important content to assess, identify and analyze dangerous location for road safety research. But until now, there is not a statistical method to identify dangerous location, which is based on a fine theoretical foundation, which is easy to use, suitable for any area. Based on the Chinese characters of road management, a statistic method for identifying dangerous location in an area or country is studied. Firstly, statistic road system is divided into four types and seriousness of accident is divided into four categories, in which indirect economic loss is included. Secondly, based on the simple Poisson distribution method, the distribution of accidents flow is determined. Lastly, according to the character of accident distribution, traffic volume, accident seriousness, economic loss and economic supporting, a nature and quantitatively determined double index is given to confirm limit values of high accident frequency and high accident rates. Dangerous location is determined by these two limit values. According to different high accident frequency and high accident rates, types of dangerous locations and their countermeasures are confirmed.

Keyword:

Roads and streets Statistical methods Highway accidents Management Location Accident prevention Poisson distribution

Author Community:

  • [ 1 ] [Hu, Jiang-Bi]Beijing Key Lab. of Traffic Engineering, Beijing University of Technology, Beijing 100097, China
  • [ 2 ] [Fei, Xue-Liang]China Highway Engineering Consulting Corporation, Beijing 100097, China
  • [ 3 ] [Liu, Xiao-Ming]Beijing Key Lab. of Traffic Engineering, Beijing University of Technology, Beijing 100097, China

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Source :

Journal of Beijing University of Technology

ISSN: 0254-0037

Year: 2007

Issue: 5

Volume: 33

Page: 465-469

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 8

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