• DocumentCode
    1798188
  • Title

    LOGAN´s Run: Lane optimisation using genetic algorithms based on NSGA-II

  • Author

    Witheridge, Simon ; Passow, Benjamin N. ; Shell, Jethro

  • Author_Institution
    Fac. of Technol., De Montfort Univ., Leicester, UK
  • fYear
    2014
  • fDate
    6-11 July 2014
  • Firstpage
    63
  • Lastpage
    68
  • Abstract
    Whilst bus lanes are an important tool to ensure bus time reliability their presence can be detrimental to urban traffic. In this paper a Non-dominated Sorting Genetic Algorithm (NSGA-II) has been adopted to study the effect of bus lanes on urban traffic in terms of location and time of operation. Due to the complex nature of this problem traditional search would not be feasible. An artificial arterial route has been modelled from real data to evaluate candidate solutions. The results confirm this methodology for the purpose of studying and identifying bus lane locations and times of operation. Additionally it is shown that bus lanes can exist on an arterial link without exclusively occupying a continuous lane for large periods of time. Furthermore results indicate a use for this methodology over a larger scale and potential near real-time operation.
  • Keywords
    genetic algorithms; public transport; road traffic; vehicle routing; LOGAN; artificial arterial route; bus lane locations; bus operation time reliability; lane optimisation using genetic algorithms based on NSGA-II; nondominated sorting genetic algorithm; urban traffic; Cities and towns; Genetic algorithms; Optimization; Roads; Sociology; Statistics; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), 2014 International Joint Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4799-6627-1
  • Type

    conf

  • DOI
    10.1109/IJCNN.2014.6889825
  • Filename
    6889825