Adaptive driving route of busses along EDSA using artificial neural network (ANN)

• Main Authors: Yasay, Bernard G., Dadios, Elmer P., Fillone, Alexis M.
• Format: text
• Published: Animo Repository 2016
• Subjects: Intelligent transportation systems; Neural networks (Computer science); Bus travel > Philippines > Metro Manila; Artificial intelligence; Manufacturing
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/1882; https://animorepository.dlsu.edu.ph/context/faculty_research/article/2881/type/native/viewcontent
• Institution: De La Salle University

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. © 2015 IEEE.