Abstract & Overview
Predicted or estimated totals of traffic volume over one or more years are required in both highway pavement and safety engineering. While current recommended practices contain guidance on how to generate such estimates, they are less clear on how to quantify the uncertainty attached to the estimates. This paper describes an initial solution to this problem. Empirical Bayes methods are used to compute quantities of the predictive probability distribution of the traffic total at a highway site, given a sample of daily traffic volumes from the site. Probable ranges and their associated probability values are readily found, and a point prediction of the total traffic can be obtained as the median, or 50th percentile, of the predictive distribution.