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final report
Traffic Congestion and Reliability: Linking Solutions to Problems
prepared for
Federal Highway Administration
prepared by
Cambridge Systematics, Inc.
100 Cambridge Park Drive, Suite 400
Cambridge, Massachusetts 02140
with
Texas Transportation Institute
date
July 19, 2004
Table of Contents
List of Tables
Table 2.1 The Worst Physical Bottlenecks in the United States 2002
Table 2.2 Effect of Treating Unreliable Travel Times on I 75 in
Central Atlanta Hypothetical
Table 3.1 Forecasts of Passenger Transportation System Activity
Table 3.2 Forecasts of Freight Transportation System Activity
Table 3.3 Growth in Interstate Highway Traffic 1992-2002
Table 4.1 Impacts of Fully Deploying Operational Strategies in Three
Urban Areas
Table 4.2 Comparison of Benefits and Costs of Fully Deploying
Operational Strategies in Three Urban Areas
Table 4.3 2001 Urban Mobility Improvement Techniques
Existing Operations
Table 4.4 2001 Mobility Improvement Techniques Full Deployment
of Operations
Table 4.5 2003 Urban Mobility Report Added Roads 2001 Data
Table 5.1 Selected FHWA Congestion Relief Resources
Table B.1 Potential Challenges to Accurately Assessing Congestion
Table B.2 Comparison of the Relative Advantages and Limitations of
Modeling Versus Measurement
List of Figures
Figure ES.1 Peak-Period Congestion (Travel Time Index) Trends
by U.S. Population Group
Figure ES.2 Weekday Peak-Period Congestion Has Grown in Several
Ways in the Past 20 Years in Our Largest Cities
Figure ES.3 Travel Time Reliability Illustration
Figure ES.4 The Sources of Congestion National Summary
Figure ES.5 Percentage of Highway Segments with over 10,000 Trucks
Per Day Comparison of 1998 to 2020
Figure 2.1 The Sources of Congestion National Summary 2-4
Figure 2.2 Actual and Improved Peak-Period Travel Times on I 75 Southbound Central Atlanta, 2002
Figure 2.3 Relationship Between Congestion Level and Reliability
Figure 3.1 Peak-Period Congestion (Travel Time Index) Trends by
U.S. Population Group
Figure 3.2 Weekday Peak-Period Congestion Has Grown in Several
Ways in the Past 20 Years in Our Largest Cities
Figure 3.3 How Many Rush Hours in a Day?
Figure 3.4 In-Vehicle Travel Times for Peak-Hour Trips Have Grown Substantially in Large Cities
Figure 3.5 Travel Time Reliability Illustration
Figure 3.6 Projected Growth in Urban Freeway Congestion
(Bottleneck-Related) under Different VMT Growth Rates, 2002-2010 (Top 78 Metro Areas)
Figure 3.7 Travel Time and Reliability Trends 2001-2002
Figure 3.8 Percentage of Highway Segments with over 10,000 Trucks
Per Day, Comparison of 1998 to 2020
Figure 3.9 2020 Congestion Forecasts, No Trucks
Figure 3.10 2020 Congestion Forecasts, With Trucks
Figure 3.11 Effect of Trucks on Delay at the 50 Worst Urban Bottlenecks
Figure 3.12 Travel Times in Central Atlanta, I 75 Southbound I 85 to I 20
Figure 3.13 Central Atlanta, I 75 Southbound Weekdays between
4:00 and 7:00 p.m.
Figure 3.14 Variations in Congestion by Time-of-Day
Figure 3.15 Average Travel Times to Work 1980-2000
Figure 3.16 Economic Effects of Transportation
Figure 4.1 A Variety of Strategies, When Used in Combination, Can Effectively Deal with Congestion
Figure 4.2 Proportion of Benefits Value of Full Operations Deployment
in Tucson
Figure 4.3 Comparison of Potential Annual Costs in Tucson,
Cincinnati, and Seattle
Figure 4.4 Observed Benefits of Ramp Meters in the Twin Cities
Figure 4.5 Reported Changes in Traffic Conditions after the Shutdown
Figure 4.6 The T Rex Project in Denver, Colorado
Figure B.1 General Taxonomy of Mobility-Based Performance Measures
Figure B.2 Modeling Versus Measurement - When Should They
Be Used?
Figure D.1 Congestion Trends on Minneapolis Freeways
Figure D.2 Congestion Trends on Atlanta Freeways
Figure D.3 Congestion Trends on Los Angeles Freeways
Figure D.4 Congestion Trends on Seattle Freeways
Figure D.5 Reliability Trends in Four Cities, 2000-2002
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