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YUAN Quan, LI Yi-bing, LU Guang-quan. Identification analysis model of traffic accident-prone locations based on geographical view angle[J]. Journal of Traffic and Transportation Engineering, 2010, 10(1): 101-105. doi: 10.19818/j.cnki.1671-1637.2010.01.018
Citation: YUAN Quan, LI Yi-bing, LU Guang-quan. Identification analysis model of traffic accident-prone locations based on geographical view angle[J]. Journal of Traffic and Transportation Engineering, 2010, 10(1): 101-105. doi: 10.19818/j.cnki.1671-1637.2010.01.018
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Identification analysis model of traffic accident-prone locations based on geographical view angle

doi: 10.19818/j.cnki.1671-1637.2010.01.018
  • 1.

    State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China

  • 2.

    School of Transportation Science and Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China

More Information
  • Author Bio:

    YUAN Quan(1974-), male, senior engineer, PhD, + 86-10-62783381, yuanq@tsinghua.edu.cn

  • Received Date: 2009-09-16
  • Publish Date: 2010-02-25
    Abstract
  • In order to evaluate traffie accident-prone locations thoroughly and establish early- warning system, the geographical view characteristics of urban road traffic system was studied. The analysis model of traffic accident-prone locations was investigated through the application of relevant methods. The meaning and structure of evaluated road traffic system was confirmed. From different layers of traffic system including spot, line and plane, basic evaluation index system was established, and the analysis model of traffic accident-prone locations was constructed by integrating common statistics method, matrix analysis method and improved quality control method. The data selections of important parameters and the output forms of analysis results were discussed, and the accident-prone locations of nine roads in some city were analyzed. Analysis result indicates that road 4 is accident-prone road, road 3 has the most accident numbers and equivalent accident numbers, and road 5 has the most accident rate. After comprehensive evaluation, roads 3, 4, 5 are identified as accident-prone roads. So the model can identify and analyze the road traffic accident-prone locations comprehensively. 3 tabs, 6 figs, 10 refs.

     

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