Cycle-by-Cycle Queue Length Estimation for Signalized Intersections Using Multi-Source Data

Zhongyu Wang¹, Qing Cai¹, Bing Wu¹, Yinhai Wang²,Linbo Li¹

(1. Key Laboratory of Road and Traffic Engineering of Ministry of Education, Tongji University, Shanghai 201804, China;2. Dept. of Civil and Environmental Engineering, University of Washington, Seattle WA 98195-2700, USA)



Abstract:

In order to estimate vehicular queue length at signalized intersections accurately and overcome the shortcomings and restrictions of existing studies especially those based on shockwave theory, a new methodology is presented for estimating vehicular queue length using data from both point detectors and probe vehicles. The methodology applies the shockwave theory to model queue evolution over time and space. Using probe vehicle locations and times as well as point detector measured traffic states, analytical formulations for calculating the maximum and minimum (residual) queue length are developed. The proposed methodology is verified using ground truth data collected from numerical experiments conducted in Shanghai, China. It is found that the methodology has a mean absolute percentage error of 17.09％, which is reasonably effective in estimating the queue length at traffic signalized intersections. Limitations of the proposed models and algorithms are also discussed in the paper.

Key words:  queue length estimation  multi-source data  traffic signals  traffic shockwave theory

DOI：10.11916/j.issn.1005-9113.2015.02.013

Clc Number:U491.26

Fund: