Urban Expressway Real-Time Traffic State Estimation and Travel Time Prediction within EKF Framework

In order to meet the need of traffic route guidance and traffic monitoring system in urban areas, this paper introduces a method to estimate and predict traffic condition and travel time between arbitrary locations by utilizing the Extended Kalman Filtering (EKF) framework. The basic concept is to first predict future traffic conditions using macroscopic dynamic models that are integrated with EKF based on the fixed traffic detectors in urban areas, and then predict actual travel time using "fictitious car" method. Finally, a case study in Shanghai is presented. The results demonstrate acceptable applicability and precision of the method. This study may lead to better traffic control and traffic route guidance, and improve the accuracy of broadcasted traffic conditions.