• DocumentCode
    8389
  • Title

    Study of intelligent load analysis system using genetic algorithm

  • Author

    Jo, Byung-Wan ; Yoon, Kwang-Won ; Lee, Yi-Shu ; Choi, Ji-Sun

  • Author_Institution
    Dept. of Civil Eng., Hanyang Univ., Seoul, South Korea
  • Volume
    8
  • Issue
    5
  • fYear
    2014
  • fDate
    Aug-14
  • Firstpage
    464
  • Lastpage
    469
  • Abstract
    Roads play a crucial role in societal infrastructure as a main artery for the economy and lives of people. However, numerous deformations are caused by an increasing number of overloaded vehicles. Accordingly, an efficient managing system for preventing overloaded vehicles could be organised by using the road as a scale by applying a genetic algorithm to analyse the load and drive information of vehicles. First, accurate analysis of loads by using the behaviour of the road itself is needed to solve illegal axle manipulation problems of overloaded vehicles and to install intelligent embedded load analysis systems. Accordingly, to use the road behaviour, the transformation in this way was measured by installing an underground box-type indoor model, and an indoor experiment was conducted by using a genetic algorithm. After five driving sessions with each vehicle, 50 sets of dynamic responding data were attained. The recognition variables were calculated to be within the error range of 10%.
  • Keywords
    automated highways; genetic algorithms; road vehicles; drive vehicle information; driving sessions; genetic algorithm; illegal axle manipulation problems; indoor experiment; intelligent embedded load analysis systems; load vehicle information; managing system; overloaded vehicles; road behaviour; societal infrastructure; underground box-type indoor model;
  • fLanguage
    English
  • Journal_Title
    Intelligent Transport Systems, IET
  • Publisher
    iet
  • ISSN
    1751-956X
  • Type

    jour

  • DOI
    10.1049/iet-its.2012.0142
  • Filename
    6870204