Estimation of dynamic assignment matrices and OD demands using adaptive Kalman Filtering

The purpose of this research was to develop a dynamic model for the on-line estimation and prediction of freeway users' origin-destination (OD) matric es. In this paper, we present a Kalman Filtering algorithm that uses time-v arying assignment matrices generated by using a mesoscopic traffic simulato r. The use of a traffic simulator to predict time-varying travel time model parameters was shown to be promising for the determination of dynamic OD m atrices for a freeway system. Moreover, the issues of using time-varying mo del parameters, effects of incorporating different sources of measurements and the use of adaptive estimation are addressed and investigated in this r esearch.