• DocumentCode
    3738149
  • Title

    Adaptive driving route of busses along EDSA using Artificial Neural Network (ANN)

  • Author

    Bernard G. Yasay;Elmer P. Dadios;Alexis M. Fillone

  • Author_Institution
    College of Engineering, Bulacan State University, City of Malolos, Philippines
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Epifanio de los Santos Avenue (EDSA) is one of the busiest national road in the Philippines millions vehicle are passing thru it every day especially in rush hour. Implementing Intelligent Transportation System (ITS) along this high way will provide a big help to every Filipino. This paper applied Artificial Intelligent (AI) and Artificial Neural Networks (ANN) to find the corresponding bus schedule depend on the parameters input value. The input parameters are Passenger volume embed (PVe), Passenger volume dispatch (PVd), Traffic congestion (Tc), Distance and Time. ANN will train with the different combination of these parameters value each combination has its corresponding schedule output. Simulation output are 00 means the station is not possible, 01 means the station is passable, 10 means that station needs an express schedule and 11 means the bus is need to reroute because of a high traffic congestion. This research will be very useful in providing ITS along EDSA using artificial intelligence and neural networks.
  • Keywords
    "Artificial neural networks","Artificial intelligence","Schedules","Mathematical model","Training","Vehicles"
  • Publisher
    ieee
  • Conference_Titel
    Humanoid, Nanotechnology, Information Technology,Communication and Control, Environment and Management (HNICEM), 2015 International Conference on
  • Type

    conf

  • DOI
    10.1109/HNICEM.2015.7393233
  • Filename
    7393233