TRB Pubsindex
Text Size:

Title:

Real-Time Queue Length Estimation for Signalized Intersections Using Vehicle Trajectory Data

Accession Number:

01628066

Record Type:

Component

Availability:

Find a library where document is available


Order URL: http://worldcat.org/isbn/9780309442114

Abstract:

Queue length is one of the most important performance measures for signalized intersections. Many methods for queue length estimation based on various data sources have been proposed in the literature. With the latest developments and applications of probe vehicle systems, cycle-by-cycle queue length estimation based only on probe data has become a promising research topic. However, most existing methods assume that information such as signal timing, arrival pattern, and penetration rate is known, an assumption that constrains their applicability in practice. The objective of this study was to propose a cycle-by-cycle queue length estimation method using only probe data without the foregoing assumption. Based on the shock wave theory, the proposed method is capable of reproducing the dynamic queue forming and dissipating process cycles at signalized intersections by using probe vehicle trajectories. To reproduce the queuing processes, the inflection points of probe vehicle trajectories representing the changes of arrival patterns are identified and extracted from the trajectory points of vehicles joining and leaving the queue. A piecewise linear function is then used to fit all the inflection points to estimate the stopping and discharging shock waves. Finally, signal timing data and queue lengths can be calculated on the basis of the estimated shock waves. Under both saturated and oversaturated traffic conditions, the performance of the method is comprehensively evaluated through 60 simulation scenarios, which cover sampling intervals from 5 s to 60 s and penetration rates ranging from 5% to 100%. Results show that compared with the method proposed by Ramezani and Geroliminis in 2015, the proposed method has more robustness for all the sampling intervals and displays more estimation accuracy of queue length and a higher success rate under conditions of low penetration rate.

Monograph Accession #:

01656418

Report/Paper Numbers:

17-02419

Language:

English

Authors:

Li, Fuliang
Tang, Keshuang
Yao, Jiarong
Li, Keping

Pagination:

pp 49–59

Publication Date:

2017

Serial:

Transportation Research Record: Journal of the Transportation Research Board

Issue Number: 2623
Publisher: Transportation Research Board
ISSN: 0361-1981

ISBN:

9780309442114

Media Type:

Digital/other

Features:

Figures (5) ; References (31) ; Tables (2)

Uncontrolled Terms:

Subject Areas:

Data and Information Technology; Highways; Operations and Traffic Management; Planning and Forecasting

Files:

TRIS, TRB, ATRI

Created Date:

Dec 8 2016 10:54AM

More Articles from this Serial Issue: