This final report presents a practical approach for dynamic origin/destination demandestimation. The proposed dynamic origin/destination estimation framework addressesmany of the shortcomings of the existing formulations and presents a formulation forgeneral networks and not just corridors. One unique feature of this framework is its useof section density as a variable instead of flow. The framework is built upon thefoundation of static origin/destination matrix estimation by adding the temporal aspect.Two traffic assignment models, namely DYNASMART and DTA are used for assigningdynamic ODs onto the network and 1-Step Kalman Filter and Least Squares methodsare used for optimizing the errors between the estimated and the true section counts. 1-Step Kalman Filter is considered as a special case of a Kalman Filter which is developedfor future work with a rolling horizon estimation framework. In addition, thisformulation also describes an infrastructure from which real-time traffic counts andother section data on various freeways could be collected and used in dynamicframeworks.
Abstract:
Publication date:
March 1, 2000
Publication type:
Research Report
Citation:
Sun, C., & Porwal, H. (2000). Dynamic Origin/Destination Estimation Using True Section Densities (UCB-ITS-PRR-2000-5). https://escholarship.org/uc/item/0f0711s6