Filtering Duplicated Location in Tracking Traffic Data

Abstract

Intelligent Transportation System (ITS) has been becoming an integral part of life in city, giving at the result of great impact by utilizing the communication, computing and sensor technologies to solve the relating problem of transportation such as traffic congestions. Traffic congestion is used to curse to citizen and an ongoing problem in almost urban areas. The purpose of this paper is mainly to provide the data without noises as much as possible to Traffic Detection System (TDS) based on GPS_enable Mobile phone. The system is constructed into two parts: Client side (Mobile device) and Cloud Backend Server. In this work, the process of transportation mode filtering is carried out on the Client side applying Moving Average Filtering method and then the filtering location duplicated data continues to work out on Server side based on the Client’s result. In order to solve the server side issue, the distance based clustering method, OPTICS: Ordering Point To Identify the Clustering Structure, is mainly utilized. Afterward, the accuracy of the system is measured by Purity, F-measurement and Entropy method. To execute closeness between GPS points, the distance between them is measured by using Haversine Formula.