2.6 Quality Assurance
Checking the quality and coherence of data is a critical part of the data collection process. The results of the analysis highly depend on the quality of data collected. It is recommended that field visits be made during the time when data is being collected. Field visits can help verify and ground truth any issues that could arise later when checking the data. They can also be helpful in documenting any atypical traffic patterns due to construction or road closures on adjacent projects, weather, debris on the road, or anything else that affects the data collection. It is recommended that the source of all data be documented, and a copy of the data be provided in the report appendix.
It is suggested that the following checks are performed once the data is collected and processed:
- Completeness – Check collected data for completeness. Does the data have all the necessary information needed for analysis? Were there errors in the data collection such as missing timing periods due to equipment malfunction or processing error? Were all modes considered?
- Accurate – Verify data is reasonable and matches field observations. Data may contain outlying or non-representative data due to equipment malfunction, post processing errors, incidents, or human errors. An example of an error that could occur with video counting equipment is U-turns being double counted at a roundabout due to the camera not being able to capture the entire roundabout.
- Discrepancy – It is recommended that all data collected such as traffic counts, speeds, or travel times be checked against other days of data collected for the same data type. If there are large variations, discrepancies, or outliers Traffic and Safety Analysis Procedures Manual | 2024 2-22 based on the comparison or what was observed in the field, then it is important to determine the cause of the discrepancy and address it accordingly. If multiple days’ worth of data is collected, it may be warranted to discard major outliers.