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Dynamic Origin/Destination Estimation Using True Section Densities

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  • Sun, Carlos
  • Porwal, Himanshu

Abstract

This final report presents a practical approach for dynamic origin/destination demand estimation. The proposed dynamic origin/destination estimation framework addresses many of the shortcomings of the existing formulations and presents a formulation for general networks and not just corridors. One unique feature of this framework is its use of section density as a variable instead of flow. The framework is built upon the foundation of static origin/destination matrix estimation by adding the temporal aspect. Two traffic assignment models, namely DYNASMART and DTA are used for assigning dynamic ODs onto the network and 1-Step Kalman Filter and Least Squares methods are 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 developed for future work with a rolling horizon estimation framework. In addition, this formulation also describes an infrastructure from which real-time traffic counts and other section data on various freeways could be collected and used in dynamic frameworks.

Suggested Citation

  • Sun, Carlos & Porwal, Himanshu, 2000. "Dynamic Origin/Destination Estimation Using True Section Densities," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt0f0711s6, Institute of Transportation Studies, UC Berkeley.
    • Handle: RePEc:cdl:itsrrp:qt0f0711s6
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    References listed on IDEAS

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