Estimating AADT Using Statewide Traffic Data Programs: Missing Data Analysis

Abstract: State highway agencies usually operate system-wide traffic monitoring programs for collecting traffic data. Of particular importance is the traffic volume data that is used in the estimation of the Annual Average Daily Traffic (AADT). State Departments of Transportation (DOTs) measure the AADT at locations of permanent ATR and WIM stations and estimate the parameter at all other locations using short-term counts. Traffic counters at the permanent ATR and WIM stations frequently malfunction and result in a specific period(s) of inaccurate or missing data. The study used ATR and WIM data from the state of Montana to examine the effect of missing data on the accuracy of AADT estimation. Specifically, ATR and WIM stations belonging to the same functional classification and with full year of traffic data were selected in this study. On a rotational basis, one station was used for testing the accuracy of AADT estimation, while the remaining stations (training stations) were used in developing the traffic adjustment factors. Data truncation at the training stations was conducted using two sampling techniques and three scenarios of data availability: one, two and three weeks of data within each month. The study results showed that the increase in AADT approximation (inaccuracy) was not linearly proportional to the increase in the amount of missing data. Given the extreme scenarios of missing data examined in this study (e.g., all permanent stations missing data simultaneously) and the relatively lower effect on AADT approximation, it can be concluded that the current practice in treating missing data does not involve a considerable compromise in the accuracy of AADT estimation.

Keywords: traffic monitoring program, AADT, missing data, adjustment factors, traffic data collection, permanent stations