Arterial Travel Time Characterization and Real-time Traffic Condition Identification Using GPS-equipped Probe Vehicles

摘要

Monitoring and predicting traffic condition on signalized urban arterials has been one of thebiggest challenges in transportation engineering. In this study, a method of arterial travel timeestimation based on multi-component mixture models and Markov Chain is presented. Inaddition, combined with travel time data collected from GPS probe vehicles, a real-time trafficcondition identification approach based on Bayes theorem is proposed. A preliminary calibrationunder two different traffic conditions of the proposed method using NGSIM data is alsoprovided. Results suggest that the proposed method can characterize the travel time of an arteriallink well and provide an accurate estimation of route mean travel time. Also a single GPS probewas able to identify real-time traffic condition successfully in most cases.