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Publication Number:  FHWA-HRT-14-057    Date:  February 2018
Publication Number: FHWA-HRT-14-057
Date: February 2018

 

Safety Evaluation of Access Management Policies and Techniques

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FOREWORD

Access management (AM) is the process that provides (or manages) access to land development while preserving safety, capacity, and speed on the surrounding road network. A growing number of agencies have included closing, consolidating, or improving driveways, median openings, and intersections as part of their AM implementation strategy. However, these same agencies are often challenged to provide rigorous justifications that explain the safety benefits of their policies, practices, and strategies.

The objective of this research was to develop crash prediction models for evaluating the safety effects of corridor AM policies and strategies on urban, suburban, and urbanizing arterials. Corridor-level crash prediction models were developed using more than 600 mi of detailed corridor data from four different regions in the United States. Agencies can use the crash prediction models to assess the safety impacts of their decisions related to corridor AM.

 

Monique R. Evans, P.E., CPM
Director, Office of Safety, Research
and Development

Notice

This document is disseminated under the sponsorship of the U.S. Department of Transportation in the interest of information exchange. The U.S. Government assumes no liability for the use of the information contained in this document.

The U.S. Government does not endorse products or manufacturers. Trademarks or manufacturers' names appear in this report only because they are considered essential to the objective of the document.

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The Federal Highway Administration (FHWA) provides high-quality information to serve Government, industry, and the public in a manner that promotes public understanding. Standards and policies are used to ensure and maximize the quality, objectivity, utility, and integrity of its information. FHWA periodically reviews quality issues and adjusts its programs and processes to ensure continuous quality improvement.

 

Technical Report Documentation Page

1. Report No.

FHWA-HRT-14-057

2. Government Accession No.

 

3 Recipient's Catalog No.

 

4. Title and Subtitle

Safety Evaluation of Access Management Policies and Techniques

5. Report Date

February 2018

6. Performing Organization Code

 

7. Author(s)

Frank Gross, Craig Lyon, Bhagwant Persaud, Jerome Gluck, Matt Lorenz, and Scott Himes

8. Performing Organization Report No.

 

9. Performing Organization Name and Address

Vanasse Hangen Bustlin, Inc. (VHB)
8300 Boone Blvd., Suite 700
Vienna, VA 22182-2626

10. Work Unit No. (TRAIS)

 

11. Contract or Grant No.

DFTH61-09-C-00026

12. Sponsoring Agency Name and Address

Office of Safety Research and Development
Federal Highway Administration
Turner-Fairbank Highway Research Center
6300 Georgetown Pike
McLean, VA 22101

13. Type of Report and Period Covered

Final Report: October 2009-October 2013

14. Sponsoring Agency Code

HRDS-10

15. Supplementary Notes

The Contracting Officer’s Representative of this project is Dr. Wei Zhang (HRDS-10). Technical panel members include Dr. Joe Bared and Neil Spiller.

16. Abstract

Access management (AM) is the process that provides (or manages) access to land development while preserving safety, capacity, and speed on the surrounding road network. These benefits have been increasingly recognized at all levels of government, and a growing number of agencies are managing access by requiring driveway permit applications and establishing where new access should be allowed. They are also closing, consolidating, or improving driveways, median openings, and intersections as part of their AM implementation strategy. However, these decisions are often challenged for various reasons, and there have been few scientifically rigorous evaluations to quantify the safety effects of corridor AM. As such, there is a need to provide additional information to help rationalize decisions related to AM so that agencies can better explain the safety benefits of their policies and practices. This study seeks to fill some of the safety-related research gaps—namely, to quantify the safety impacts of corridor AM decisions.

 

The objective of this research was to evaluate the safety effects of corridor AM policies and strategies on urban, suburban, and urbanizing arterials. Crash prediction models were developed using more than 600 mi of detailed corridor data from four different regions in the United States. The crash prediction models were estimated using generalized linear modeling. Agencies can use the crash prediction models to assess the safety impacts of their decisions related to corridor AM.

17. Key Words

Access management, safety analysis, crash prediction models

18. Distribution Statement

No restrictions. This document is available to the public through NTIS: National Technical Information Service, Springfield, VA 22161.
http://www.ntis.gov

19. Security Classification
(of this report)

Unclassified

20. Security Classification
(of this page)

Unclassified

21. No. of Pages

176

22. Price

 

Form DOT F 1700.7 (8-72) Reproduction of completed page authorized

SI* (Modern Metric) Conversion Factors

 

TABLE OF CONTENTS

CHAPTER 1. INTRODUCTION

CHAPTER 2. STUDY OBJECTIVE AND SCOPE

CHAPTER 3. METHODOLOGY

CHAPTER 4. DATA COLLECTION

CHAPTER 5. SUMMARY STATISTICS

CHAPTER 6. ANALYSIS

CHAPTER 7. RESULTS

CHAPTER 8. GUIDANCE FOR PRACTICAL APPLICATION OF THE MODELS

CHAPTER 9. SAMPLE PROBLEMS TO ILLUSTRATE THE USE OF THE MODELS

CHAPTER 10. CALIBRATION

CHAPTER 11. VALIDATION

CHAPTER 12. SAFETY EVALUATION TOOL AND FUNCTIONAL SPECIFICATIONS

CHAPTER 13. CONCLUSIONS

APPENDIX A. HSIS VARIABLES OBTAINED FOR EACH STATE

APPENDIX B. FIELD DATA COLLECTION PROTOCOL

APPENDIX C. SUMMARY OF MODELS BY LAND USE AND CRASH TYPE

APPENDIX D. SUMMARY STATISTICS BY LAND USE AND REGION

APPENDIX E. CORRELATION COEFFICIENTS BY LAND USE

REFERENCES

LIST OF FIGURES

Figure 1. Illustration. Unsignalized driveway spacing.
Figure 2. Illustration. Comparison of uniform and nonuniform signal spacing (figure 5 in Gluck, Levinson, and Stover, 1999).(3)
Figure 3. Illustration. Intersection physical area versus functional area (adapted from Transportation Research Circular 456, figure 4).(4)
Figure 4. Illustration. Allowable traffic movements before and after raised median installation (figure 30 in Gluck, Levinson, and Stover, 1999).(3)
Figure 5. Illustration. Potential frontage road configuration.
Figure 6. Illustration. Improved access configuration with cross connectivity.
Figure 7. Graph. Relationship between total access points per mile and crash rate (figure 24 in Gluck, Levinson, and Stover, 1999).(3)
Figure 8. Graph. Relationship between access points per mile and crash rate (figure 26 in Gluck, Levinson, and Stover, 1999).(3)
Figure 9. Graph. Relationship between signals per mile and crash rate (figure 6 in Gluck, Levinson, and Stover, 1999).(3)
Figure 10. Photo. Example of an urban arterial in a residential area.
Figure 11. Photo. Example of a suburban arterial in a commercial area.
Figure 12. Illustrations and photos. Verifying HSIS data with aerial photos.(15)
Figure 13. Screen shot. Verifying data with aerial imagery.(16)
Figure 14. Photo. Verifying data with video.
Figure 15. Image. Example of point objects for a 1-mi corridor.(17)
Figure 16. Photo. Data collection equipment used for field visit.
Figure 17. Equation. General form of crash prediction model.
Figure 18. Equation. Crash prediction model with regional calibration.
Figure 19. Equation. Normalized crash prediction model with regional calibration.
Figure 20. Equation. Formula to estimate effects of variables of interest for existing conditions.
Figure 21. Equation. Formula to estimate w.
Figure 22. Equation. Formula to estimate the annual expected crash frequency (EB estimate).
Figure 23. Equations. Calculation of predicted right-angle crashes/year (existing).
Figure 24. Equations. Calculation of predicted right-angle crashes/year (proposed).
Figure 25. Equations. Effect of ACCDENS: predicted total crashes/year (existing).
Figure 26. Equations. Effect of ACCDENS: predicted total crashes/year (proposed).
Figure 27. Equations. Effect of PROPNODEV: predicted total crashes/year (existing).
Figure 28. Equations. Effect of PROPNODEV: predicted total crashes/year (proposed).
Figure 29. Equations. Total crashes: predicted total crashes/year (existing).
Figure 30. Equations. Total crashes: predicted crashes/year (proposed).
Figure 31. Equations. Turning crashes: predicted turning crashes/year (existing).
Figure 32. Equations. Turning crashes: predicted turning crashes/year (proposed).
Figure 33. Equations. Right-angle crashes: predicted right-angle crashes/year (existing).
Figure 34. Equations. Right-angle crashes: predicted right-angle crashes/year (proposed).
Figure 35. Equations. Baseline predicted right-angle crashes/year (existing alternative A).
Figure 36. Equations. Estimate of w.
Figure 37. Equations. Expected right-angle crashes/year (existing alternative A).
Figure 38. Equation. Estimate EB correction factor.
Figure 39. Equations. Predicted right-angle crashes/year (existing alternative A).
Figure 40. Equations. Predicted right-angle crashes/year (proposed alternative B).
Figure 41. Equations. Predicted right-angle crashes/year (proposed alternative C).
Figure 42. Equations. Adjusted predicted right-angle crashes/year for existing condition.
Figure 43. Equations. Expected right-angle crashes/year for proposed condition.
Figure 44. Equations. Baseline predicted right-angle crashes/year (existing).
Figure 45. Equation. Estimate of the impacts of the variables of interest for existing conditions.
Figure 46. Equations. Estimation of multipliers.
Figure 47. Equations. Adjusted predicted right-angle crashes/year (existing alternative A).
Figure 48. Equations. Estimation of multipliers.
Figure 49. Equations. Adjusted predicted right-angle crashes/year (proposed alternative B).
Figure 50. Equation. Estimated calibration factor.
Figure 51. Equation. Original multiplier.
Figure 52. Equation. Estimation of calibrated multiplier.
Figure 53. Equations. Minnesota crash prediction model.

LIST OF TABLES

Table 1. Prioritization of AM policies and techniques.
Table 2. Strategies/policies in relation to AM safety principles (adapted from V.G. Stover, 2007).(1)
Table 3. Area type and land use categories.
Table 4. Potential issues and opportunities related to cross-sectional studies.
Table 5. Objects and characteristics coded in ArcGIS™.
Table 6. Number of corridors by area type and land use.
Table 7. Mileage of corridors by area type and land use.
Table 8. Crash type definitions.
Table 9. North Carolina mileage by area type and land use.
Table 10. Summary statistics for North Carolina independent variables.
Table 11. Summary statistics for North Carolina dependent variables.
Table 12. Northern California mileage by area type and land use.
Table 13. Summary statistics for Northern California independent variables.
Table 14. Summary statistics for Northern California dependent variables.
Table 15. Southern California mileage by area type and land use.
Table 16. Summary statistics for Southern California independent variables.
Table 17. Summary statistics for Southern California dependent variables.
Table 18. Minnesota mileage by area type and land use.
Table 19. Summary statistics for Minnesota independent variables.
Table 20. Summary statistics for Minnesota dependent variables.
Table 21. Overview of mixed-use models by crash type.
Table 22. Overview of commercial models by crash type.
Table 23. Overview of residential models by crash type.
Table 24. Relevant models by crash type of interest—mixed land use.
Table 25. Relevant models by crash type of interest—commercial land use.
Table 26. Relevant models by crash type of interest—residential land use.
Table 27. Correlation coefficients for MINSPCSIG (model coefficient, p-value).
Table 28. Correlation coefficients for NOLTLSIG (model coefficient, p-value).
Table 29. Driveway density CMFs inferred from the Highway Safety Manual predictive models for multivehicle crashes on urban four-lane undivided and divided arterials.(22)
Table 30. Comparison of implied CMFs for SIGDENS.
Table 31. HSIS data obtained for California.
Table 32. HSIS data obtained for Minnesota.
Table 33. HSIS data obtained for North Carolina.
Table 34. Alternate model 1 for mixed-use total crashes.
Table 35. Alternate model 2 for mixed-use total crashes.
Table 36. Alternate model 3 for mixed-use total crashes.
Table 37. Alternate model 1 for mixed-use injury crashes.
Table 38. Alternate model 2 for mixed-use injury crashes.
Table 39. Alternate model 1 for mixed-use turning crashes.
Table 40. Alternate model 2 for mixed-use turning crashes.
Table 41. Alternate model 3 for mixed-use turning crashes.
Table 42. Alternate model 1 for mixed-use rear-end crashes.
Table 43. Alternate model 2 for mixed-use rear-end crashes.
Table 44. Alternate model 1 for mixed-use right-angle crashes.
Table 45. Alternate model 2 for mixed-use right-angle crashes.
Table 46. Alternate model 3 for mixed-use right-angle crashes.
Table 47. Alternate model 1 for commercial total crashes.
Table 48. Alternate model 2 for commercial total crashes.
Table 49. Alternate model 1 for commercial injury crashes.
Table 50. Alternate model 2 for commercial injury crashes.
Table 51. Alternate model 3 for commercial injury crashes.
Table 52. Alternate model 4 for commercial injury crashes.
Table 53. Alternate model 1 for commercial turning crashes.
Table 54. Alternate model 2 for commercial turning crashes.
Table 55. Alternate model 1 for commercial rear-end crashes.
Table 56. Alternate model 2 for commercial rear-end crashes.
Table 57. Alternate model 1 for commercial right-angle crashes.
Table 58. Alternate model 2 for commercial right-angle crashes.
Table 59. Alternate model 1 for residential total crashes.
Table 60. Alternate model 2 for residential total crashes.
Table 61. Alternate model 3 for residential total crashes.
Table 62. Alternate model 4 for residential total crashes.
Table 63. Alternate model 1 for residential injury crashes.
Table 64. Alternate model 2 for residential injury crashes.
Table 65. Alternate model 1 for residential turning crashes.
Table 66. Alternate model 2 for residential turning crashes.
Table 67. Alternate model 3 for residential turning crashes.
Table 68. Alternate model 4 for residential turning crashes.
Table 69. Alternate model 1 for residential rear-end crashes.
Table 70. Alternate model 2 for residential rear-end crashes.
Table 71. Alternate model 3 for residential rear-end crashes.
Table 72. Alternate model 1 for residential right-angle crashes.
Table 73. Alternate model 2 for residential right-angle crashes.
Table 74. Alternate model 3 for residential right-angle crashes.
Table 75. Summary statistics for North Carolina mixed-use land use.
Table 76. Summary statistics for Minnesota mixed-use land use.
Table 77. Summary statistics for Northern California mixed-use land use.
Table 78. Summary statistics for Southern California mixed-use land use.
Table 79. Summary statistics for North Carolina commercial land use.
Table 80. Summary statistics for Minnesota commercial land use.
Table 81. Summary statistics for Northern California commercial land use.
Table 82. Summary statistics for Southern California commercial land use.
Table 83. Summary statistics for North Carolina residential land use.
Table 84. Summary statistics for Minnesota residential land use.
Table 85. Summary statistics for Northern California residential land use.
Table 86. Summary statistics for Southern California residential land use.
Table 87. Correlation coefficients for mixed land use.
Table 88. Correlation coefficients for commercial land use.
Table 89. Correlation coefficients for residential land use.

LIST OF ABBREVIATIONS AND SYMBOLS

4D four-lane divided arterial
4U four-lane undivided arterial
AADT annual average daily traffic
AASHTO American Association of State Highway and Transportation Officials
ACCDENS number of driveways plus unsignalized intersections per mile
ADT average daily traffic
AM access management
AVGAADT average of the annual average daily traffic
b coefficient estimated for the annual average daily traffic term in the models
ci vector of coefficients estimated for independent variables included in the models
CMF crash modification factor
DRWYDENS number of driveways per mile
EB empirical Bayes
FHWA Federal Highway Administration
GIS Geographic Information System
GLM generalized linear modeling
GPS Global Positioning System
HSIS Highway Safety Information System
ID identity
k dispersion parameter
MAXSPCSIG maximum spacing of signalized intersections
MEDOPDENS number of median openings per mile
MEDOPLT number of median openings with a left-turn lane
MEDOPNOLT number of median openings without a left-turn lane
MINSPCSIG minimum spacing of signalized intersections
MVMT million vehicle-miles traveled
NO3LEGFULLUNSIG number of three-legged full-movement unsignalized intersections
NO3LEGLFMOUNSIG number of three-legged unsignalized intersections with no left-turn movement from crossroad
NO3LEGLIMUNSIG number of three-legged limited-movement unsignalized intersections
NO3LEGRIROUNSIG number of three-legged right-in/right-out unsignalized intersections
NO3LEGSIG number of three-legged signalized intersections
NO3LEGUNSIG number of three-legged unsignalized intersections
NO4LEGFULLUNSIG number of four-legged full-movement unsignalized intersections
NO4LEGLFMOUNSIG number of four-legged unsignalized intersections with no left-turn movement from crossroad
NO4LEGLIMUNSIG number of four-legged limited-movement unsignalized intersections
NO4LEGRIROUNSIG number of four-legged right-in/right-out unsignalized intersections
NO4LEGSIG number of four-legged signalized intersections
NO4LEGUNSIG number of four-legged unsignalized intersections
NO5LEGSIG number of five-legged signalized intersections
NO5LEGUNSIG number of five-legged unsignalized intersections
NOCOMFULLDRWY number of commercial full-movement driveways
NOCOMLIMDRWY number of commercial limited-movement driveways
NODRWYS number of driveways
NOLTLSIG number of signalized intersections with a left-turn lane on the mainline
NOLTLUNSIG number of unsignalized intersections with a left-turn lane
NOMEDOP number of median openings
NOMEDOPLT number of median openings with a left-turn lane
NOMEDOPNOLT number of median openings without a left-turn lane
NORESFULLDRWY number of residential full-movement driveways
NORESLIMDRWY number of residential limited-movement driveways
NORTLSIG number of signalized intersections with a right-turn lane on the mainline
NORTLUNSIG number of unsignalized intersections with a right-turn lane
NOSIG number of signalized intersections
NOUNSIG number of unsignalized intersections
PC personal computer
PROPDIV proportion of corridor length with divided median
PROPFRONTRD proportion of corridor length with a frontage road
PROPFULLDEV proportion of corridor length with full roadside development
PROPLANE1 proportion of corridor length with two lanes
PROPLANE2 proportion of corridor length with three or four lanes
PROPLANE3 proportion of corridor length with five or more lanes
PROPLIGHT proportion of corridor length with illumination present
PROPLIMCONN proportion of corridor length with limited connectivity on adjacent developments
PROPMODCONN proportion of corridor length with moderate connectivity on adjacent developments
PROPNODEV proportion of corridor length with no roadside development
PROPPARTDEV proportion of corridor length with partial adjacent development
PROPPOORPVMNT proportion of corridor length with a poor pavement condition
PROPSIGCONN proportion of corridor length with significant connectivity on adjacent developments
PROPTWLTL proportion of corridor length with two-way left-turn lane
PROPUNDIV proportion of corridor length with an undivided median
PROPVC proportion of corridor length with visual clutter
SIGDENS number of signalized intersections per mile
SPCOFFLT minimum spacing from off-ramp to available left turn onto mainline from same side of road
SPCOFFRT minimum spacing from off-ramp to available right turn onto mainline from same side of road
SPCON minimum spacing from on-ramp to available right turn onto mainline from same side of road
SPEED_ LIMIT posted speed limit
TWLTL two-way left-turn lane
UNSIGDENS number of unsignalized intersections per mile
USGS United States Geological Survey
vpd vehicles per day
w EB weight
Xi vector of independent variables included in the model

 

 

 

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