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Mathematical Problems in Engineering
Volume 2012 (2012), Article ID 892575, 12 pages
http://dx.doi.org/10.1155/2012/892575
Research Article

A Method for Queue Length Estimation in an Urban Street Network Based on Roll Time Occupancy Data

1College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China
2School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150091, China
3College of Traffic and Transportation, Jilin University, Changchun 130022, China

Received 15 May 2012; Revised 19 August 2012; Accepted 26 August 2012

Academic Editor: Wuhong Wang

Copyright © 2012 Dongfang Ma et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

A method estimating the queue length in city street networks was proposed using the data of roll time occupancy. The key idea of this paper is that when the queue length in front of the queue detector becomes longer, the speeds of the following vehicles to pass through the detector will become smaller, resulting in higher occupancy with constant traffic intensity. Considering the relationship between queue lengths and roll time occupancy affected by many factors, such as link length, lane width, lane number, and bus ratio, twelve different conditions were designed, and the traffic data under different conditions was obtained using VISSIM simulation. Based on the analysis of simulation data, an S-type logistic model was decided to develop for the relationship between queue lengths and roll time occupancy, and the fitting equations were obtained under the twelve simulation situations. The average model for the relationship between queue lengths and roll time occupancy was presented by successive multiple linear regression with the fitting equation parameters and simulation parameters, and the estimation model for queue length was presented through analyzing the equation of the average relation model.