Shockwave-Based Queue Estimation Approach For Undersaturated And Oversaturated Signalized Intersections Using Multi-Source Detection Data

Keywords

multi-source detection data; queue length; traffic shockwave theory; traffic signals

Abstract

With the progress of information and sensing technologies, estimating vehicular queue length at signalized intersections becomes feasible and has attracted considerable attention. The existing studies provided a solid theoretical foundation for the estimation; however, the studies have some restrictions or limitations more or less. This paper presents a new methodology for estimating vehicular queue length at signalized intersections using multi-source detection data under both undersaturated and oversaturated conditions. The methodology applies the shockwave theory to model queue dynamics. Using data from probe vehicles and point detectors, analytical formulations for calculating the maximum and minimum (residual) queue lengths of each cycle are developed. Ground truth data were collected from numerical experiments conducted at two intersections in Shanghai, China, to verify the proposed methodology. It is found that the methodology has mean absolute percentage errors of 17.09% and 12.28%, respectively, for maximum queue length estimation in two tests, which are reasonably effective. However, the methodology is unsatisfactory in estimating the residual queue length. Other limitations of the proposed models and algorithms are also discussed in the paper.

Publication Date

5-4-2017

Publication Title

Journal of Intelligent Transportation Systems: Technology, Planning, and Operations

Volume

21

Issue

3

Number of Pages

167-178

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1080/15472450.2016.1254046

Socpus ID

85002170028 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85002170028

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