Estimating Queue at Traffic Signals
Johannes J. Bezuidenhout, Prakash Ranjitkar*, Roger Dunn
Identifiers and Pagination:Year: 2014
First Page: 73
Last Page: 82
Publisher Id: TOTJ-8-73
Article History:Received Date: 24/7/2014
Revision Received Date: 21/10/2014
Acceptance Date: 22/10/2014
Electronic publication date: 09/12/2014
Collection year: 2014
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: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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.