Queue data is recommended for oversaturated conditions. Traffic count data documents the volume processed at an intersection or at a cross-sectional point on a road but not necessarily the demand. In oversaturated conditions, the volume served at an intersection or at a cross-sectional point on a road may be lower than the overall demand. It is recommended that queue data be collected for oversaturated approaches or roadway segments within the study limits. If the queues extend past the study limits, collect data upstream, past the longest queues. For severely congested corridors with extremely long queues extending past the study area, engineering judgement would be used to determine where to set study limits and data collection locations for queues.

Queues are often measured in terms of arrival and departure volumes at a given facility. Counts are typically conducted in five-minute intervals, starting before the existence of any congestion or queues at the location and ending after all queues have been cleared from the facility. The resultant queue is defined as the difference between the five-minute arrivals and departures, and arrival data is counted upstream of the longest expected queue.

Complementary ways to determine queues include conducting license plate studies; using probe-based data to look at speeds, automated traffic recorders (ATR), segment counts, travel times, and bottleneck locations; and conducting field observations or scanning Google Maps for congestion. Google Maps provides live traffic data as well as typical historical congestion levels. This may be used to get a general understanding of queues. It is recommended to perform field observations to supplement the data collected via Google Maps.