A new estimation method for multi-section traffic states of freeway

To accurately estimate multi-section traffic states of freeway, a new multi-section error state equations are built up. In the new model, error propagations of both the traffic density and the average velocity are considered and the extended Kalman filter is used to estimate all traffic states. To avoid a series of high-dimension problems, a modified weighted Gram-Schmidt orthogonal U-D factorization method is used for the time update and measurement update of the extended Kalman filter to get high numerical stability and computational efficiency. Considered the structure of system matrix, block matrix is used in U-D factorization algorithm. Results of simulation to 100 section states of freeway and actual application show that the new method can be efficiently used to estimation and prediction freeway traffic flows.