United States Department of Transportation
i
Detecting Traffic Data Anomalies in Longitudinal Signal Performance Measures
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2022-11-01
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[PDF-3.24 MB]
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Edition:Final Report, Nov 2020 to Nov 2022
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Abstract:The Utah Department of Transportation (UDOT) has continuously invested in traffic signal performance evaluation in Utah. The Brigham Young University (BYU) transportation research team developed a high-level scoring system to evaluate signal performance using four Automated Traffic Signal Performance Measures (ATSPM), including platoon ratio, split failures, arrivals on green, and red-light actuations. The scoring system helps UDOT engineers and planners to evaluate the performance of each signal. However, there is still a need to understand how intersections and corridors perform over time. Therefore, the purpose of this research was to use the scoring system developed in the previous research to analyze the signal performance longitudinally. The method described in this research expanded the study area from 20 to 32 signalized intersections and the study period from 24 days to 2 years. One additional ATSPM (approach volume) was also included. The BYU research team developed an interactive data visualization tool to show the change in signal performance measures over time, and several data anomalies were discovered in the ATSPM datasets. The research team applied linear regression, moving average and standard deviation, and distribution comparison methods to identify the data anomalies. However, due to the various types of data anomalies, only the moving average and standard deviation method was successful in identifying most of the data anomalies. Future investigation is needed to address the data anomalies and improve the data accuracy.
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