Estimating Queue at Traffic Signals

Johannes J. Bezuidenhout, Prakash Ranjitkar*, Roger Dunn
Department of Civil and Environmental Engineering, University of Auckland, New Zealand.

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Creative Commons License
© 2014 Bezuidenhoutet al;

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the Department of Civil and Environmental Engineering, University of Auckland, New Zealand; Tel: 61 9 9233515; Fax: 649 3737462; E-mail:


This paper proposes a new queue prediction model based on the data that can be collected from a single loop detector positioned at the stop line of signalised intersections. A number of different model forms were explored using an enhanced NGSIM dataset. These data were filtered to represent the data that can be typically collected from a stop line detector loop. The best six models resulted in an accuracy ranging from 83% to 95% to correctly predict the state of vehicle’s discharge close to the stop line that is whether it is a queued or platooned vehicle. When combined with a logical filter to group sequential vehicles, it enables a traffic controller to estimate the most likely queue length. The proposed model will form part of a new offset optimizer algorithm currently under development.

Keywords: Logistic regression, queue estimation, SCATS, single loop detectors.