Interactive multiple model ensemble Kalman filter for traffic estimation and incident detection

This paper studies the problem of real-time traffic estimation and incident detection by posing it as a hybrid state estimation problem. An interactive multiple model ensemble Kalman filter is proposed to solve the sequential estimation problem, and to accommodate the switching dynamics and nonlinearity of the traffic incident model. The effectiveness of the proposed algorithm is evaluated through numerical experiments using a perturbed traffic model as the true model. The supporting source code is available for download at https://github.com/Lab-Work/IMM_EnKF_Traffic_Estimation_Incident_Detection.