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A key input to many advanced traffic management operations strategies are origin-destination (OD) matricies. In order to examine the possibility of estimating OD matricies in real-time, two constrained OD estimators, based on generalized least squares and Kalman filtering, were developed and tested. A one-at-a-time processing method was introduced to provide an efficient organized framework for incorporating observations from multiple data sources in real-time. The estimators were tested under different conditions based on the type of prior OD information available, the type of assignment available, and the type of link volume model used. The performance of the Kalman filter estimators also was compared to that of the generalized least squares estimator to provide insight regarding their performance characteristics relative to one another for given scenarios. Automatic vehicle identification (AVI) tag counts were used so that observed and estimated OD parameters could be compared. While the approach was motivated using AVI data, the methodology can be generalized to any situation where traffic counts are available and origin volumes can be estimated reliably.

Highway Capacity Manual (HCM) 2000 two-lane rural highway directional, two-way, and passing-lane analysis procedures based on field data and simulation were evaluated. Detailed field data were collected from two highway sections in northern Idaho, one with and one without passing lanes. The TWOPAS simulation model was used to provide additional insights. Particular attention was given to the differences in estimates for percent time spent following (PTSF) produced by the twoway and directional analysis procedures. It was found that the two-way analysis procedure was more accurate, although both procedures produced estimates that were too high. The passing-lane analysis procedure was also evaluated, and the HCM 2000 procedure was found to be conservative in its estimates of PTSF reductions due to a passing lane.

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