• DocumentCode
    498188
  • Title

    Study on the Traffic Safety Intelligent Warning Technologies and Methods Based on the Integrated Traffic Safety Data

  • Author

    Zhu, Yin

  • Author_Institution
    Traffic Manage. Eng. Dept., Chinese People´´s Public Security Univ., Beijing, China
  • fYear
    2009
  • fDate
    25-26 April 2009
  • Firstpage
    136
  • Lastpage
    139
  • Abstract
    In this paper the traffic safety warning technologies and methods are studied deeply based on the macro-forecast and micro-forecast methods. The macro-forecast will realize the traffic safety warning based on the macro-data such as the number of traffic accidents, the death toll and the number of motor vehicles owned and so on. And the micro-forecast is based on the micro-data such as traffic flow volume, speed and density and so on. The paper introduced the integrated forecast method combined with time series method and regression forecast method to realize the macro-traffic safety warning. Moreover the simulation technology is used to realize the micro-traffic safety warning technology. Finally, the feasibility and effectiveness of that method and technology which is presented in this paper are demonstrated by an example.
  • Keywords
    regression analysis; time series; traffic engineering computing; integrated traffic safety data; macrodata; macroforecast methods; microforecast methods; motor vehicles; regression forecast method; time series method; traffic accidents; traffic flow volume; traffic safety intelligent warning technologies; Data engineering; Deductive databases; Engineering management; Health and safety; Linear regression; Road accidents; Road safety; Technology management; Traffic control; Vehicle safety; integrated traffic safety data; intelligent warning technologies and methods; traffic safety;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Database Technology and Applications, 2009 First International Workshop on
  • Conference_Location
    Wuhan, Hubei
  • Print_ISBN
    978-0-7695-3604-0
  • Type

    conf

  • DOI
    10.1109/DBTA.2009.113
  • Filename
    5207797