Sistema de reconhecimento de padrões para identificação de porte de veículos através de análise de perfil magnético

Abstract

Currently, transit agencies use traffic monitoring systems to reduce traffic accidents and as a fundamental tool for collecting statistical data for planning and management of road systems. These data are observed as the amount of information vehicles that travel at a certain point, the average speed and the identification of the category of vehicles. The identification of the category of vehicles that travels on a path allows you to control access lanes connecting to a specific class of vehicles. The objective of this work is to propose a solution for vehicle classification by analyzing signals collected from inductive sensors at the time the vehicle passes over the sensors. This set of signs for each vehicle is called the magnetic profile. This work used a classifier based on Artificial Neural Network (ANN) to identify the type of vehicle according to the pattern of magnetic profile collected. The implemented system used a Java framework that enabled the integration of ANN to the application that operates in the traffic monitoring equipment. It was developed a Java application that trains the ANN using data collected in the equipment and also allows evaluating further classification results obtained by the ANN. The vehicles were classified into the following categories: motorcycles, small vehicles, medium vehicles, buses and trucks. The developed system has been integrated into a traffic monitoring equipment manufactured by Fotosensores® and gave satisfactory results with an overall success rate above 97%. It represents an improvement in the equipment that carried out the classification.