An adaptive freeway traffic state estimator and its real-data testing part 1: basic properties

This paper addresses the real-data testing of a real-time adaptive freeway traffic state estimator that is based on macroscopic traffic flow modelling and extended Kalman filtering. It is the aim of the paper to investigate the basic properties of the traffic state estimator, including its tracking capabilities, the significance of the on-line model parameter estimation, its sensitivity to the initial values of the estimated model parameters and to the related standard deviation values.