Estimating Intersection Control Delay Using Large Data Sets of Travel Time from a Global Positioning System

Abstract

Historically, stopped delay was used to characterize the operation of intersection movements because it was relatively easy to measure. During the past decade, the traffic engineering community has moved away from using stopped delay and now uses control delay. That measurement is more precise but quite difficult to extract from large data sets if strict definitions are used to derive the data. This paper evaluates two procedures for estimating control delay. The first is based on a historical approximation that control delay is 30% larger than stopped delay. The second is new and based on segment delay. The procedures are applied to a diverse data set collected in Phoenix, Arizona, and compared with control delay calculated by using the formal definition. The new approximation was observed to be better than the historical stopped delay procedure; it provided an accurate prediction of control delay. Because it is an approximation, this methodology would be most appropriately applied to large data sets collected from travel time studies for ranking and prioritizing intersections for further analysis.