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Title:

Fundamental Diagram Calibration: A Stochastic Approach to Linear Fitting

Accession Number:

01520204

Record Type:

Component

Availability:

Transportation Research Board Business Office

500 Fifth Street, NW
Washington, DC 20001 United States

Abstract:

A statistical learning methodology is proposed for characterizing and identifying key parameters of the fundamental diagram that describes the dependence of traffic flow (or speed) on traffic density in a roadway section, based on traffic data obtained from a vehicle detection station. The proposed fundamental diagram characterization not only provides the expected value of flow (or speed) given a density measurement, but also a random probability distribution of the flow (or speed) given the density measurement. The former can be used to conduct deterministic traffic flow simulations, while the later can be used to conduct statistical flow simulation studies, by using first order traffic flow models such as the cell transmission model.

Supplemental Notes:

This paper was sponsored by TRB committee AHB45 Traffic Flow Theory and Characteristics.

Monograph Accession #:

01503729

Report/Paper Numbers:

14-4928

Language:

English

Corporate Authors:

Transportation Research Board

500 Fifth Street, NW
Washington, DC 20001 United States

Authors:

Phegley, Brian
Gomes, Gabriel
Horowitz, Roberto

Pagination:

14p

Publication Date:

2014

Conference:

Transportation Research Board 93rd Annual Meeting

Location: Washington DC
Date: 2014-1-12 to 2014-1-16
Sponsors: Transportation Research Board

Media Type:

Digital/other

Features:

Figures; References

Uncontrolled Terms:

Fundamental diagram

Subject Areas:

Highways; Operations and Traffic Management; I71: Traffic Theory

Source Data:

Transportation Research Board Annual Meeting 2014 Paper #14-4928

Files:

TRIS, TRB, ATRI

Created Date:

Jan 27 2014 3:44PM