Estimating AADT Using Statewide Traffic Data Programs: Missing Data Impact

State highway agencies usually measure Annual Average Daily Traffic (AADT) using traffic data from permanent detector stations within their system-wide traffic monitoring programs. Agencies also estimate the AADT at many other locations using short-term counts. Traffic counters at the permanent stations frequently malfunction, leading to periods of inaccurate or missing data. Addressing missing data in estimating AADT by highway agencies is important for sustainable infrastructure management. This study used extensive traffic data from permanent detector stations in the state of Montana to examine the effect of missing data on the accuracy of AADT estimation. On a rotational basis, one station was used to test the accuracy of AADT estimation, while the remaining stations (training stations) were used to develop the traffic adjustment factors. Data truncation at the training stations was conducted using two sampling techniques and three scenarios of data availability. The study results showed that the increase in AADT estimation error (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 and the relatively lower effect on AADT estimation error, it can be concluded that the current practice in treating missing data does not involve a considerable compromise in the accuracy of AADT estimation. This highlights the robustness of the current estimation practice, suggesting that it can be effectively applied in statewide traffic monitoring programs without a significant loss of accuracy.