Traffic jam warning messages from measured vehicle data with the use of three-phase traffic theory

Abstract

Based on Kerner's three-phase theory, we study an algorithm for the generation of traffic jam warming messages from measured GPS and GSM probe vehicle data that have been collected in TomTom's HD-traffic service both from nomadic devices and vehicle's embedded systems. We find that the data allows us to reconstruct the structure of congested traffic patterns with a much greater quality of spatiotemporal resolution than has been possible before. It occurs that congested traffic in measured traffic patterns consists of the two traffic phases of Kerner's three-phase theory, synchronized flow and wide moving jams. The application method distinguishes between the fronts of the congested traffic phases, wide moving jam and synchronized flow. It will be shown that a penetration of about 2% of the total traffic flow is enough to implement a precise traffic jam warning message for navigation systems.