Short-term traffic prediction with visitor location registry data

Abstract

Increasing road traffic is a major issue in current world. In this paper, we propose a set of prediction models that can perform short term traffic prediction for a given road segment. These prediction models have been developed using Neural Networks (NN), Bayesian Networks, Hidden Markov Models, variations of Regression and ensemble approaches of these models. CCTV records are used for validation of the results based on which a maximum accuracy of 85% was achieved.