Simple Methodology for Estimating Queue Lengths at Signalized Intersections Using Detector Data

Abstract

A simple methodology estimates queue length on an approach to a signalized intersection. This method has a minimal set of data requirements—flow, occupancy, cycle length, and detector setback—in contrast to prevailing methods that use detailed data defined on a per signal cycle basis to estimate vehicle trajectories. The key element of the algorithm is the estimation of two baseline occupancies that correspond to the relative position of the queue with respect to the detector location. The results of the algorithm were evaluated through traffic simulation and were also compared with field observations. Comparison of the queue estimates suggests that the detector location would be ideal for estimating queues if under prevailing conditions the tail of the queue is routinely longer than the detector setback. For detectors with appropriate setback, queue estimates match well in both comparisons. This algorithm was developed as part of the Midtown in Motion project and is operational in New York City as one of the elements of the active traffic management system.