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Title:

DAY-TO-DAY TRAVEL-TIME TRENDS AND TRAVEL-TIME PREDICTION FROM LOOP-DETECTOR DATA

Accession Number:

00802517

Record Type:

Component

Availability:

Transportation Research Board Business Office

500 Fifth Street, NW
Washington, DC 20001 United States

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Order URL: http://worldcat.org/isbn/0309066999

Abstract:

An approach is presented for estimating future travel times on a freeway using flow and occupancy data from single-loop detectors and historical travel-time information. Linear regression, with the stepwise-variable-selection method and more advanced tree-based methods, is used. The analysis considers forecasts ranging from a few minutes into the future up to an hour ahead. Leave-a-day-out cross-validation was used to evaluate the prediction errors without underestimation. The current traffic state proved to be a good predictor for the near future, up to 20 min, whereas historical data are more informative for longer-range predictions. Tree-based methods and linear regression both performed satisfactorily, showing slightly different qualitative behaviors for each condition examined in this analysis. Unlike preceding works that rely on simulation, real traffic data were used. Although the current implementation uses measured travel times from probe vehicles, the ultimate goal is an autonomous system that relies strictly on detector data. In the course of presenting the prediction system, the manner in which travel times change from day to day was examined, and several metrics to quantify these changes were developed. The metrics can be used as input for travel-time prediction, but they also should be beneficial for other applications, such as calibrating traffic models and planning models.

Supplemental Notes:

This paper appears in Transportation Research Record No. 1717, Highway and Traffic Safety: Crash Data, Analysis Tools, and Statistical Methods.

Language:

English

Corporate Authors:

Transportation Research Board

500 Fifth Street, NW
Washington, DC 20001 United States

Authors:

Kwon, J
Coifman, B
Bickel, P

Pagination:

p. 120-129

Publication Date:

2000

Serial:

Transportation Research Record

Issue Number: 1717
Publisher: Transportation Research Board
ISSN: 0361-1981

ISBN:

0309066999

Features:

Figures (7) ; References (13) ; Tables (1)

Uncontrolled Terms:

Subject Areas:

Data and Information Technology; Highways; Planning and Forecasting; I72: Traffic and Transport Planning

Files:

TRIS, TRB, ATRI

Created Date:

Nov 15 2000 12:00AM

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