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SHRP 2 L03 [Completed]

Analytic Procedures for Determining the Impacts of Reliability Mitigation Strategies

  Project Data
Funds: $1,749,998
Research Agency: Cambridge Systematics, Inc.
Principal Investigator: Richard Margiotta
Effective Date: 2/27/2007
Completion Date: 4/30/2010

Project snapshot. More details below.

Products
(Project Number)
Impact on Practice
Product Status
ANALYTIC PROCEDURES FOR DETERMINING THE IMPACTS OF RELIABILITY MITIGATION STRATEGIES (L03)

A foundation study that defines reliability, presents recommended reliability measures derived from travel time distributions, presents the causes of congestion, explains how to build a data base for estimating prediction models, conducts before and after studies of operations and capacity improvements, and develops two sets of prediction models based on empirical data from numerous metropolitan areas.
This fundamental study has already influenced research and practice through the definitions of travel time reliability it offers and how one can effectively think about the variability of travel time. This study develops models for predicting travel time reliability. The simple prediction model that comes from this research has many uses in sketch planning, simulation, and initial evaluations of operations and other expenditures. The richer model has been incorporated into the SHRP 2 Reliability spreadsheet tool to evaluate how different design treatments affect reliability.
The report is available at http://www.trb.org/Main/Blurbs/166935.aspx.

Project L33 will pilot test and validate the L03 data rich and data poor models.

Staff Responsibility: William Hyman

Reliability of transport, especially the ability to reach a destination within a certain amount of time, is a regular concern of travelers and shippers. The definition of reliability used in this research is how travel time varies over time. Agencies are increasingly aware of the issue of reliability, although the transportation industry as a whole as yet lacks a firm understanding of the causes of unreliable travel times and solutions to restore reliability. As the agenda for the SHRP 2 research on travel time reliability took shape, it became clear that a fundamental study was required to be able to talk about travel time reliability in a meaningful way.

The objective of this project was to develop technical relationships between reliability improvement strategies and reliability performance metrics.

Basic reliability issues are addressed in this study, which is not concerned with average travel times, but with ways of describing travel times that reflect the uncertainty in the amount of time required to travel between two points. Some of the uncertainty is systematic, such as the normal ebb and flow of traffic within the course of a work day or season of the year. This research shows how to derive performance measures from such distributions and recommends a set for use by managers, planners, and systems operators. The research reexamines the composition of the congestion puzzle in terms of the fractions attributable to recurrent and various sources of nonrecurrent congestion. The project team used before-and-after studies to determine the effectiveness of different types of actions, both operational and capacity enhancements, in improving reliability. This study also examined the effect of the downturn of the economy on travel time reliability. Finally, this research resulted in two types of models that can be used to estimate or predict travel time reliability. These models have broad applicability to planning, programming, and systems management and operations

Status: The project is complete.

Product Availability: Analytical Procedures for Determining the Impacts of Reliability Mitigation Strategies, SHRP 2 Report S2-L03-RR-1, was published in January 2013.  It is available as an Adobe PDF.  A printed version is available through the TRB bookstore.  An e-book version of the report is available for purchase at Google, iTunes, and Amazon.  A fact sheet and project brief are also available.

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This page was last modified on March 28, 2014.

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