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The July 2004 Report - Traffic Congestion and Reliability: Linking Solutions to Problems is still available for viewing.
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final report
Traffic Congestion and Reliability:
Trends and Advanced Strategies for Congestion Mitigation
prepared for
Federal Highway Administration
prepared by
Cambridge Systematics, Inc.
100 Cambridge Park Drive, Suite 400
Cambridge, Massachusetts 02140
with
Texas Transportation Institute
date
September 1, 2005
Table of Contents
List of Tables
Table ES.1 Reliability Statistics, Atlanta, Georgia (2000-2003)
Table 2.1 Factors Contributing to Extreme Congestion
Table 2.2 Example Congestion Performance Metrics
Table 3.1 Most Freeway Corridors in Seattle, Washington and Atlanta, Georgia
Have Experienced a Growth in Congestion and Unreliable Travel.
Table 3.2 The Worst Physical Bottlenecks in the United States
Table 4.1 The Effectiveness of CHART's Traffic incident Management on
Average Incident Duration
Table 4.2 Total Direct Benefits to Maryland Highway Users in Year 2002
Table 6.1 Selected FHWA Operations Congestion Mitigation Resources
List of Figures
Figure ES.1 Congestion Has Grown Substantially in U.S. Cities over
the Past 20 Years
Figure ES.2 The Sources of Congestion
Figure ES.3 Weekday Travel Times
Figure ES.4 Distribution of Travel Times, State Route 520 Seattle, Eastbound,
4:00-7:00 p.m. Weekdays (11.5 Miles Long)
Figure ES.5 Weekday Peak-Period Congestion Has Grown in Several Ways in
the Past 20 Years in Our Largest Cities
Figure 2.1 The Number and Duration of Incidents Varies Greatly from Day to
Day
Figure 2.2 Traffic Levels Vary Substantially over the Course of a Week
Figure 2.3 Anatomy of Congestion
Figure 2.4 Relationship of Incident and Bottleneck Delay to Traffic Intensity
Figure 2.5 Distribution of Travel Times, State Route 520 Seattle, Eastbound,
4:00-7:00 p.m. Weekdays (11.5 Miles Long)
Figure 2.6 Weekday Travel Times
Figure 2.7 Is It a Good Day or Bad Day for Commuting: Comparing Current
Travel Times to Historical Conditions
Figure 2.8 Congestion and Unreliable Travel Have Increased on I-75
Southbound in Central Atlanta, Georgia
Figure 2.9 Measuring Travel Time Is the Basis for Congestion Measures
Figure 2.10 Example of the Newly Designed Urban Congestion Report Used by
FHWA to Track Monthly Changes in Congestion
Figure 2.11 Interstate 5 Average Travel Rate for Trucks: 10-Mile Segments
Figure 3.1 Results of Two Modeling Studies to Estimate Congestion by Source
Figure 3.2 The Sources of Congestion
Figure 3.3 Congestion Has Grown Substantially in U.S. Cities over the
Past 20 Years
Figure 3.4 Peak-Period Congestion Trends by Urban Area Population Group
Figure 3.5 Weekday Peak-Period Congestion Has Grown in Several Ways in the
Past 20 Years in Our Largest Cities
Figure 3.6 How Many Rush Hours in a Day?
Figure 3.7 Travel Time Reliability Illustration
Figure 3.8 The Average Commute Travel Time in a Privately Owned Vehicle
(POV) Has Increased
Figure 3.9 The Average Commute Trip Length in a POV Has Increased
Figure 3.10 After Showing Modest Improvement in the 1990s, Average Commute
Speeds Have Begun to Worsen
Figure 3.11 Trips in San Francisco Are Now Taking Longer to Complete
Figure 3.12 Daily and Monthly Trends in Congestion
Figure 3.13 Annual Trends in Congestion
Figure 3.14 Corridor Statistics for Seattle and Atlanta
Figure 3.15 Interchange Capacity Bottlenecks on Freeways Used as Urban Truck Corridors
Figure 3.16 Congested Highways (1998)
Figure 3.17 Potentially Congested Highways (2020)
Figure 3.18 Vehicle-Miles of Travel on Major Rural and Urban Roads Increased Between 1990 to 2002
Figure 4.1 A Variety of Strategies, When Used in Combination, Can Effectively Deal with Congestion
Figure 4.2 Springfield Interchange Congestion Management Plan Budget Breakdown
Figure 4.3 Road Commission of Oakland County Road Condition Web Site Map
Figure 4.4 SCATS Hardware Structure
Figure 4.5 Milwaukee Area Freeway Web Site Map
Figure 4.6 CHART's Traffic incident Mapping Interface
Figure 4.7 Sample Drilldown Map from CHART
Figure 4.8 Reduction in Delays Due to CHART Operations
Figure 4.9 Houston's SAFEclear Program Has Improved Incident Response Times
Figure 4.10 Cost of Wasted Fuel and Time on Katy Freeway under Alternative Construction Scenarios
Figure 5.1 Reusing Real-Time Operations Data, Used Initially in Control Strategies, Is an Effective Way of Monitoring Performance and Providing Data for Future Assessments
Figure 5.2 Percentage of Maryland Lane-Miles with Average Annual Volumes Below Congested Levels
Figure 5.3 Example of Seattle's Portrayal of Historic Congestion Patterns
Figure 5.4 Example Minnesota Dashboard
Figure 5.5 Planning for Operations
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