A network analysis of road traffic with vehicle tracking data

Abstract

The high resolution tracking data for hundreds to thousands of urban vehicles, as well as the availability of digitized map data, provide urban planners unprecedented opportunities for better understanding urban motor vehicle transportation and for better exploiting the knowledge thereof. This paper combines the domain knowledge of traffic engineering with machine learning techniques, and gives a new approach to the problem of traffic speed estimation and travel time prediction.