Collecting volume and classification data on interstate facilities poses an often-ignored problem: keeping field technicians and commuters safe. To the dismay of QC and our partners, some count firms will eagerly oblige these requests in the form of cheap, intrusive tube counts. While tube counts are the tried and true method to collect throughput data at a low cost, their very presence on interstates increases safety concerns, and thereby financial risk to the requesting firm or agency. To make matters worse, typical interstate volumes exceed the collection limits of even the most expensive tube counters, resulting in unclassifiable or missed vehicles and skewed classification distributions. So how does QC meet the need for comparably robust datasets while addressing the safety challenges of busy, high speed facilities?

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Recent advancements in automated and manual video processing, side-fire radars, and other passive devices are part of the answer. We no longer have to worry about disrupting traffic flow for installation, tubes being torn in the roadway, or dislodged nails puncturing tires. However, new hardware and processing methods are not without their downsides. Video processing can be expensive, and automation has not resolved the challenges of occlusion, poor weather, sun glare and detecting unusual traffic incidents. Side-fire radars may underperform in heavily congested areas and are susceptible to signal deflection from stationary objects. Ground-level radar and infrared can collect and process only a limited number of lanes and classifications, precluding deployments on interstates.

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The best solution involves a combination of corroborating and complementary approaches that are catered to the roadway geometry and traffic conditions at each location. One of these approaches must involve visual validation, the cornerstone of QC’s quality control plan. For example, side-fire radars will provide length-based classification data sets for days, weeks or months at a time and serve well as a primary collection method. At the same time, manual video counting is used for supplemental, axle-based datasets during peak hours. Video counts also serve as a substitute to side-fire radars for locations where deflection or severe queuing is a concern. This combined approach effectively addresses the safety and accuracy issues associated with tube count deployments, improves data reliability during peak traffic flow, keeps the cost low relative to a video-only approach and offers a more granular dataset during critical periods.

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Instead of relying on one tool, engineers and agencies should have access to a suite of corroborating methods to accommodate the variety of facilities, vehicle speeds, data schemas and budgets assigned to every project. Safety and data integrity should always be prioritized above cost. As a result, data collection firms can significantly mitigate safety and accuracy risks associated with each method, build confidence in the data provided and build a better foundation for engineering studies.

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See it in action: I-77 Express Lane Expansion - The North Carolina Turnpike Authority (NCTA) plans to widen I-77 from six lanes to ten lanes by constructing Express Lanes from I-485 (Exit 1) to I-277/NC 16 (Exit 11). The total project length is 9.6 miles with a projected cost of $1.2B and a tentative construction start date in 2027. In order to prepare preliminary designs, engineers needed traffic data to forecast the impact on the interchanges over the 9.6 miles. Quality Counts was tasked with delivering one of the largest corridor data collection projects we ever performed. QC collected, processed, and delivered:

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• 116 13-Hour Turning Movement Counts (TMCs) using cameras
• 34 48-hour volume, speed, and classification datasets using tube counters
• 32 48-Hour video counts of ramp intersections using cameras
• 20 48-Hour mainline counts using radars side-fire radars
• 20 16-hour mainline radar verification counts using cameras
• Total Video Processing Hours = 5,500

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The I-77 corridor between the SC state line and the I-85 interchange experiences frequent congestion during the AM and PM peaks. This less than optimal vehicle flow rate sometimes tricks radars into recording multiple vehicles traveling closely together as one large articulated truck, resulting in lower than expected volumes and skewed classification distributions. In order to improve data accuracy for this project, QC utilized a combination of radar collection with peak hour manual video verification at every mainline location. In total, our team collected and processed over 5,500 hours of video in a span of 2.5 months.

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