Advances in origin-destination trip table estimation for transportation planning and traffic simulation

Abstract

Dynamic transportation models are becoming widespread owing to the ready access to powerful computing resources. This has led to the increasing use of Dynamic Traffic Assignment (DTA) and traffic simulation for a variety of planning applications. Timevarying origin-destination (OD) trip tables are key inputs to such models. However, they are generally not directly observed and must be estimated from other traffic measurements such as counts. We discuss several dynamic OD estimation approaches found in the literature and describe one of the more recent methodologies in detail. This method was tested in the TransModeler traffic simulation package using two examples: a small case study with simulated data, and a real network and count data from the I-5 corridor in California. The results confirm that dynamic OD estimation is hard in practice, but can provide significant improvements over the current state of the practice.

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