A Formulation of Neural Network Diagram Based on Origin-Destination Matrix Focusing on Traffic Management Optimization on Paranaque City

EasyChair Preprint 4055

Abstract

Urban challenges like traffic congestion and a failed transportation system are some of the leading problems in the Philippines in the past decades in which these affect the daily lives of the Filipino citizens.  In this paper, the researchers evaluate the overall transportation system of Parañaque City by identifying the existing problems and providing solutions. This study also considers the extensive analysis of origin-destination matrix, vehicle count, population and etc. as these help the researchers formulate a Neural Network strategy.Through the analysis of data and information, the researchers have determined the factors affecting the transportation system and also the congested areas around the city. The avenues of Dr.Arcadio Santos, Quirino and Baclaran are the congested areas wherein these are caused by various factors such as lack of discipline, violators, increase in car ownership, population growth, and the lack of public (parking) space as well. And as part of the paper, the researchers propose or recommend some solutions that may solve the transportation problems in Parañaque City.

Keyphrases: Parañaque City, neural network, peak hour volume, strategy OD matrix, traffic congestion

@booklet{EasyChair:4055,
  author    = {Ethan Roy Gabriel and Paul Diony Tolentino and Cymon Francis Yan},
  title     = {A Formulation of  Neural Network Diagram Based on Origin-Destination Matrix Focusing on Traffic Management Optimization on Paranaque City},
  howpublished = {EasyChair Preprint 4055},
  year      = {EasyChair, 2020}}