Travel time is an important performance measure for transportation facilities. The objective of this research is to develop a model for estimating travel time for signalized arterials using probabilistic modeling. The model provides travel time based on the cycle length, green times, link lengths, maximum operating speed, offsets, acceleration/deceleration rate, and the per lane entering flow rate at each intersection. Results from the model were compared to a field data-calibrated simulator, and it was concluded that travel times from the simulation and the analytical model are similar and have similar trends. Increases in the g/C ratio and the acceleration/deceleration rate result in decreasing travel time. The impacts of other factors, such as link length, speed, and flow rate are not consistent: they mostly depend on the prevailing offsets. It was concluded that the analytical model can estimate the arterial travel time and its variability with reasonable accuracy.
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