Skip to main navigation Skip to search Skip to main content

Identification analysis model of traffic accident-prone locations based on geographical view angle

  • Quan Yuan*
  • , Yi Bing Li
  • , Guang Quan Lu
  • *Corresponding author for this work
  • Tsinghua University

Research output: Contribution to journalArticlepeer-review

Abstract

In order to evaluate traffic 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.

Original languageEnglish
Pages (from-to)101-105+126
JournalJiaotong Yunshu Gongcheng Xuebao/Journal of Traffic and Transportation Engineering
Volume10
Issue number1
StatePublished - Feb 2010

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Geographical view angle
  • Identification analysis model
  • Traffic accident-prone location
  • Traffic safety

Fingerprint

Dive into the research topics of 'Identification analysis model of traffic accident-prone locations based on geographical view angle'. Together they form a unique fingerprint.

Cite this