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SEMCOG’s Innovative Traffic Data Quality Assurance/Quality Control and Automated AADT Estimation Reduce Labor Costs Associated with Converting and Entering Data

Publication Year: 2017


Background

This case study highlights two noteworthy practices at the Southeast Michigan Council of Governments (SEMCOG) regarding short-duration traffic count validation procedures and an automated annual average daily traffic (AADT) estimation process. SEMCOG maintains a centralized traffic count database and receives traffic counts from the local agencies in southeast Michigan. SEMCOG conducts 46 validity checks on all traffic count data to identify invalid data available in the database but not adequate for analysis. After implementing the system, SEMCOG reduced labor costs associated with converting and entering data and was able to spend more time analyzing data. SEMCOG developed an algorithm that works inside its geographic information system (GIS) to improve AADT estimates by searching for uncounted segments with nearby counted segments. When a counted segment is identified, the algorithm calculates the weighted average of two nearby segments and assigns that AADT to the uncounted segment. This process was automated using Python scripts, which results in an increase in the number of AADT estimates without requiring additional field data collection.

Read the Case Study Southeast Michigan Council of Governments: Innovative Traffic Data Quality Assurance/Quality Control Procedures and Automating AADT Estimation for more detailed information.

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Contact

Stuart Thompson
Federal Highway Administration
202-366-8090
Stuart.Thompson@dot.gov

Publication Year: 2017

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