Travel and Emissions Impacts of Highway Operations Strategies

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Contact Information: OperationsFeedback@dot.gov

U.S. Department of Transportation
Federal Highway Administration
Office of Operations
1200 New Jersey Avenue, SE
Washington, DC 20590
www.ops.fhwa.dot.gov

Publication #: FHWA-HOP-14-013

March 2014

Table of Contents

Executive Summary

Purpose and Background

Study Approach

Conclusions

Recommendations

Chapter 1. Introduction

Purpose of the Study

Organization of This Report

Background to the Issues: Operations Strategies, Demand, and Emissions

Study Approach

Chapter 2. Current Knowledge Base

Introduction

Literature Review

The Impact of Capacity and Operations Improvements on Travel Time, Travel-Time Reliability, and Traveler Behavior

Implications of Induced Demand For Estimating Impacts and Social/User Benefits

Effect of Accessibility on Land Use Patterns

Chapter 3. Atlanta Case Study: Demand Effects of Operational Improvements

Purpose of The Case Study Analysis

Background

Data Sources

Results

Chapter 4. Reliability-Land Use

Introduction

Methodology

Household and Firm Location Choices

Estimation Results

Sensitivity Analysis with Urbansim

References

Chapter 5. Short-Term Emissions Impacts Of Operations Strategies

Overview

Study Design

Results

Chapter 6. Long-Term Regional Impacts Of Operations Strategies

Introduction

Methodology

Regional Modeling Results

I-15 Traffic Simulation Analysis with Updated Demand

Chapter 7. Conclusions And Recommendations

Conclusions

Recommendations

List of Tables

Table 1. Types of analyses and experiments considered for the study.

Table 2. Characteristics of existing advanced modeling frameworks considered.

Table 3. Comparison of modal emissions models.

Table 4. Ability of activity-based modeling frameworks to accommodate demand shifts.

Table 5. Value of travel time variability.

Table 6. Travel time elasticities from a tour-based travel demand model.

Table 7. Estimated performance measures for base case and alternatives.

Table 8. User benefits.

Table 9. Number of objects per dataset used in the Bay Area SCS implementation.

Table 10. Deployment of operational strategies on Atlanta study sections.

Table 11. Change in Congestion Level and Demand on Study Sections

Table 12. Summary of quarterly trends.

Table 13. Summary of before/after volume trends at ATR Site 11

Table 14. Summary of before/after volume trends at ATR Site 229

Table 15. Summary of before/after volume trends at ATR Site 272

Table 16. Summary of before/after volume trends at ATR Site 307

Table 17. Summary of before/after volume trends at ATR Site 308

Table 18. Variables in the hedonic regressions.

Table 19. Variables in the residential location choice models.

Table 20. Variables in the nonresidential location choice models.

Table 21. Residential hedonic models.

Table 22. Non-residential hedonic models.

Table 23. Residential location choice models.

Table 24. Nonresidential location choice models by industry.

Table 25. Operations deployment scenarios.

Table 26. Operations deployment scenario results compared to baseline.

Table 27. Primary analysis scenarios for the I-15 simulations.

Table 28. Emission results for primary scenarios, 2010 (nonincident scenarios).

Table 29. System Performance Measures, 6:00 a.m. to 9:00 a.m., 2010 (nonincident scenarios).

Table 30. Emission results for primary scenarios, 2010 (incident scenarios).

Table 31. System performance measures, 6:00 a.m. to 9:00 a.m., 2010 (incident scenarios).

Table 32. Freeway delay (vehicle hours).

Table 33. Freeway delay (vehicle hours).

Table 34. Capacity equivalents for operations strategies.

Table 35. AM peak period performance results, 2010 MTC Model runs.

Table 36. MTC model VMT by time period and strategy.

Table 37. Congested VMT proportions, 2015 Bay Area network.

Table 38. AM Peak Period performance results, 2015 MTC Model runs.

Table 39. Bay Area regional trip making, 2015.

Table 40. Demand changes applied to I-15 scenarios.

Table 41. I-15 Traffic simulation results with increased demand, nonincident scenarios

Table 42. I-15 Traffic simulation results with increased demand, incident scenarios.

List of Figures

Figure 1. Flowchart. Final study approach, advanced modeling phase.

Figure 2. Flowchart. The activity-based modeling framework from SHRP 2 C10B.

Figure 3. Flowchart. Final study approach, advanced modeling phase.

Figure 4. Equation. Ninety-fifth percentile.

Figure 5. Graph. The travel time distribution is the basis for defining reliability metrics.

Figure 6. Scatter graph. Correlation between 95^th percentile TTI and mean TTI.

Figure 7. Equation. SHRP 2 Project CO₄’s generalized highway utility function.

Figure 8. Equation. TTE.

Figure 9. Flowchart. Effects of a facility improvement on level of service, travel volume, and externalities.

Figure 10. Bar graph. Change in arterial through traffic travel times.

Figure 11. Flowchart. Interaction of information in an urban system.

Figure 12. Map. Atlanta NaviGAtor coverage, 2011.

Figure 13. Map. Urban Interstate ATRs in the Atlanta region.

Figure 14. Graph. SHRP Section 1.0, PM peak.

Figure 15. Graph. SHRP Section 2.0, AM peak.

Figure 16. Graph. SHRP Section 5.0, AM peak.

Figure 17. Graph. SHRP Section 6.0, PM peak.

Figure 18. Graph. SHRP Section 7.0, PM peak.

Figure 19. Graph. SHRP Section 8.0, AM peak.

Figure 20. Graph. SHRP Section 9.0, PM peak.

Figure 21. Graph. SHRP Section 10, AM peak.

Figure 22. Graph. I‑85 Northside SB, AM peak.

Figure 23. Graph. I‑85 Northside NB, PM peak.

Figure 24. Map. San Francisco Bay Area.

Figure 25. Equation. Log(Pi).

Figure 26. Equation. U subscript i.

Figure 27. Equation. P subscript i.

Figure 28. Equation. Travel rate.

Figure 29. Equation. MeanTTI prime.

Figure 30. Equation. MeanTTI superscript 80.

Figure 31. Map. Links modified for scenarios.

Figure 32. Graph. CMEM’s link-level fuel consumption modeling methodology.

Figure 33. Map. Study area I‑15 corridor in San Diego, California.

Figure 34. Map. Location and geographic boundaries of corridor

Figure 35. Map. Incident setup.

Figure 36. Scatter graph. CO₂ emission rates from MOVES outputs, freeways.

Figure 37. Scatter graph. CO₂ emission rates from MOVES outputs, arterials.

Figure 38. Line graph. Demand profile at the analysis bottleneck.

Figure 39. Map and graph. Speed profile under normal demand, no VSL.

Figure 40. Map and graph. Speed profile under high demand, no VSL.

Figure 41. Map and graph. Speed profile under normal demand with traditional VSL.

Figure 42. Map and graph. Speed profile under high demand with traditional VSL.

Figure 43. Map and graph. Speed profile under normal demand with nontraditional VSL.

Figure 44. Map and graph. Speed profile under high demand with nontraditional VSL.

Figure 45. Flowchart. Final study approach, advanced modeling phase

Figure 46. Equation. Speed.

Figure 47. Equation. Speed.

Figure 48. Graph. Comparison of selected speed-flow curves.

Figure 49. Equation. Two-lane freeways.

Figure 50. Equation. Three-lane freeways.

Figure 51. Equation. Four-lane freeways.

Figure 52. Equation. Adjusted incident delay.

Figure 53. Equation. Adjusted incident delay; adjusted total delay.

Figure 54. Flowchart. Regional emission modeling using the MTC model.

Figure 55. Map. Households.

Figure 56. Map. Employment.