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Monitoring and Predicting Freeway Travel Time Reliability: Using Width and Skew of Day-to-Day Travel Time Distribution
Cover of Monitoring and Predicting Freeway Travel Time Reliability: Using Width and Skew of Day-to-Day Travel Time Distribution

Accession Number:

01014808

Record Type:

Component

Availability:

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Washington, DC 20001 United States
Order URL: http://www.trb.org/Main/Public/Blurbs/156722.aspx

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Order URL: http://worldcat.org/isbn/0309093902

Abstract:

Generally, the day-to-day variability of route travel times on, for example, freeway corridors is considered closely related to the reliability of a road network. The more that travel times on route r are dispersed in a particular time-of-day (TOD) and day-of-week (DOW) period, the more unreliable travel times on route r are conceived to be. In the literature, many different aspects of the day-to-day travel time distribution have been proposed as indicators of reliability. Mean and variance do not provide much insight because those metrics tend to obscure important aspects of the distribution under specific circumstances. It is argued that both skew and width of this distribution are relevant indicators for unreliability; therefore, two reliability metrics are proposed. These metrics are based on three characteristic percentiles: the 10th, 50th, and 90th percentile for a given route and TOD-DOW period. High values of either metric indicate high travel time unreliability. However, the weight of each metric on travel time reliability may be application- or context-specific. The practical value of these particular metrics is that they can be used to construct so-called reliability maps, which not only visualize the unreliability of travel times for a given DOW-TOD period but also help identify DOW-TOD periods in which congestion will likely set in (or dissolve). That means identification of the uncertainty of start, end, and, hence, length of morning and afternoon peak hours. Combined with a long-term travel time prediction model, the metrics can be used to predict travel time (un)reliability. Finally, the metrics may be used in discrete choice models as explanatory variables for driver uncertainty.

Monograph Title:

Data Initiatives

Monograph Accession #:

01014803

Language:

English

Authors:

van Lint, J W C
van Zuylen, Henk J

Pagination:

pp 54-62

Publication Date:

2005

Serial:

Transportation Research Record: Journal of the Transportation Research Board

Issue Number: 1917
Publisher: Transportation Research Board
ISSN: 0361-1981

ISBN:

0309093902

Media Type:

Print

Features:

Figures (8) ; References (16)

Subject Areas:

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

Files:

TRIS, TRB, ATRI

Created Date:

Dec 27 2005 8:57AM

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