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Title:

Arterial Travel Time Characterization and Real-time Traffic Condition Identification Using GPS-equipped Probe Vehicles

Accession Number:

01334296

Record Type:

Component

Abstract:

Monitoring and predicting traffic condition on signalized urban arterials has been one of the biggest challenges in transportation engineering. In this study, a method of arterial travel time estimation based on multi-component mixture models and Markov Chain is presented. In addition, combined with travel time data collected from global positioning system (GPS) probe vehicles, a real-time traffic condition identification approach based on Bayes theorem is proposed. A preliminary calibration under two different traffic conditions of the proposed method using Next Generation Simulation (NGSIM) data is also provided. Results suggest that the proposed method can characterize the travel time of an arterial link well and provide an accurate estimation of route mean travel time. Also a single GPS probe was able to identify real-time traffic condition successfully in most cases.

Monograph Accession #:

01329018

Report/Paper Numbers:

11-2018

Language:

English

Corporate Authors:

Transportation Research Board

500 Fifth Street, NW
Washington, DC 20001 United States

Authors:

Feng, Yiheng
Davis, Gary A
Hourdos, John

Pagination:

15p

Publication Date:

2011

Conference:

Transportation Research Board 90th Annual Meeting

Location: Washington DC, United States
Date: 2011-1-23 to 2011-1-27
Sponsors: Transportation Research Board

Media Type:

DVD

Features:

Figures; Maps; References (14) ; Tables (1)

Uncontrolled Terms:

Traffic conditions

Subject Areas:

Highways; Operations and Traffic Management; Planning and Forecasting; I72: Traffic and Transport Planning

Source Data:

Transportation Research Board Annual Meeting 2011 Paper #11-2018

Files:

TRIS, TRB

Created Date:

Feb 17 2011 6:01PM