Estimation of Road Traffic Congestion using GPS Data

Abstract

Road traffic congestion is headache major problem in urban area of both developing and developed countries. In order to reduce this problem, traffic congestion states of road networks are estimated so that congested road can be avoided. In this paper, we estimate the real time traffic congestion states of user’s desired source and destination and present the estimated results in Google Map. We use Hidden Markov model (HMM) for estimating the traffic condition states of these road network using both historical and real time data. To get these traffic data we use GPS trajectories data collected from mobile phones on vehicles. We evaluate our estimating system using dataset generated by collect data from phone-equipped vehicles over a period of 4 months in Yangon.