Mixture Kalman filter based highway congestion mode and vehicle density estimator and its application

We present our latest results on developing and implementing a traffic congestion mode and vehicle density estimator for a segment of Interstate 210 in Southern California. Using a mixture Kalman filtering (MKF) algorithm on the switching-mode traffic model, the estimator is able to provide estimated vehicle densities at unmeasured locations, as well as the congestion statuses (free-flow or congested), which are not directly observed. The program runs efficiently, thus making it possible to carry out estimation in real time.