Analysis reveals missing data minimally affects accuracy of AADT estimation from traffic data in Montana, suggesting current methods remain effective.
State highway agencies usually measure Annual Average Daily Traffic (AADT) using traffic data from permanent detector stations that are part of 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 and result in periods of inaccurate or missing data. 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 for testing the accuracy of AADT estimation, while the remaining stations (training stations) were used in developing the traffic adjustment factors. Data trunca-tion 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 ap-proximation (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 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.
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Qureshi et al. (2025) studied this question.
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