Application of a Markov Chain Traffic Model to the Greater Philadelphia Region

Abstract

A macroscopic traffic model based on the Markov chain process is developed for urban traffic networks.  The method utilizes existing census data rather than measurements of traffic to create parameters for the model.  Four versions of the model are applied to the Philadelphia regional highway network and evaluated based on their ability to predict segments of highway that possess heavy traffic.