• DocumentCode
    2063309
  • Title

    A Research about Traffic Safety Character of two-lane highway in Plain Area Basing on Random-effect negative binomial model

  • Author

    Zhang Tie-jun ; Dan, Liu

  • Author_Institution
    M.O.C., Beijing, China
  • Volume
    3
  • fYear
    2010
  • fDate
    14-15 Aug. 2010
  • Firstpage
    385
  • Lastpage
    389
  • Abstract
    This paper reviews the studies which have been performed in two-lane highway traffic safety research, and select random-effect negative binomial model to illustrate the traffic safety character of two-lane highway in plain area. More than 1380 kilometers(about 56 highways) two-lane highways in Beijing and Shandong province are investigated and the traffic safety data are collected, such as accident data, geometric data and roadside data. The highways are divided into 1772 segments. The result shows that the random-effect negative binomial model provides a better result than basic model. It is also illustrated that percent of motorcycle in traffic, the percent of truck in traffic, whole driveway density of the highway where the segment is involved, the percent of village length in a highway, driveway density of each sample are associated with higher total accident occurrence, and the width of road surface, the percent of bicycle in traffic tend to point to lower total accident occurrence.
  • Keywords
    road accidents; road safety; road traffic; traffic engineering computing; Beijing; Shandong province; accident data; geometric data; random-effect negative binomial model; roadside data; traffic safety character; two-lane highway traffic safety research; Accidents; Analytical models; Data models; Predictive models; Roads; Safety; accident prediction mod; highway; random-effect negative binomial model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Engineering (ICIE), 2010 WASE International Conference on
  • Conference_Location
    Beidaihe, Hebei
  • Print_ISBN
    978-1-4244-7506-3
  • Electronic_ISBN
    978-1-4244-7507-0
  • Type

    conf

  • DOI
    10.1109/ICIE.2010.269
  • Filename
    5571597