Developing a Guide for Rural Highways: Reliability and Quality of Service Evaluation Methods (2024)
Chapter: Front Matter
Developing a Guide for
Rural Highways
RELIABILITY AND QUALITY OF
SERVICE EVALUATION METHODS
Scott S. Washburn
University of Florida
Gainesville, FL
Ahmed Al-Kaisy
Sajid Raza
Montana State University
Bozeman, MT
Ana Moreno
Technical University of Munich
Munich, Germany
Jorge Barrios
Kittelson & Associates, Inc.
Orlando, FL
Bastian Schroeder
Kittelson & Associates, Inc.
Wilmington, NC
Conduct of Research Report for NCHRP Project 08-135
Submitted September 2023
NCHRP
Web-Only Document 392
Developing a Guide for Rural Highways
RELIABILITY AND QUALITY OF SERVICE EVALUATION METHODS
Scott S. Washburn
University of Florida
Gainesville, FL
Ahmed Al-Kaisy
Sajid Raza
Montana State University
Bozeman, MT
Ana Moreno
Technical University of Munich
Munich, Germany
Jorge Barrios
Kittelson & Associates, Inc.
Orlando, FL
Bastian Schroeder
Kittelson & Associates, Inc.
Wilmington, NC
Conduct of Research Report for NCHRP Project 08-135
Submitted September 2023
© 2024 by the National Academy of Sciences. National Academies of Sciences, Engineering, and Medicine and the graphical logo are trademarks of the National Academy of Sciences. All rights reserved.
Digital Object Identifier: https://doi.org/10.17226/27897
NATIONAL COOPERATIVE HIGHWAY RESEARCH PROGRAM
Systematic, well-designed, and implementable research is the most effective way to solve many problems facing state departments of transportation (DOTs) administrators and engineers. Often, highway problems are of local or regional interest and can best be studied by state DOTs individually or in cooperation with their state universities and others. However, the accelerating growth of highway transportation results in increasingly complex problems of wide interest to highway authorities. These problems are best studied through a coordinated program of cooperative research.
Recognizing this need, the leadership of the American Association of State Highway and Transportation Officials (AASHTO) in 1962 initiated an objective national highway research program using modern scientific techniques—the National Cooperative Highway Research Program (NCHRP). NCHRP is supported on a continuing basis by funds from participating member states of AASHTO and receives the full cooperation and support of the Federal Highway Administration (FHWA), United States Department of Transportation, under Agreement No. 693JJ31950003.
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DISCLAIMER
The opinions and conclusions expressed or implied in this report are those of the researchers who performed the research. They are not necessarily those of the Transportation Research Board; the National Academies of Sciences, Engineering, and Medicine; the FHWA; or the program sponsors.
The Transportation Research Board does not develop, issue, or publish standards or specifications. The Transportation Research Board manages applied research projects which provide the scientific foundation that may be used by Transportation Research Board sponsors, industry associations, or other organizations as the basis for revised practices, procedures, or specifications.
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The information contained in this document was taken directly from the submission of the author(s). This material has not been edited by TRB.
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COOPERATIVE RESEARCH PROGRAMS
CRP STAFF FOR NCHRP WEB-ONLY DOCUMENT 392
Waseem Dekelbab, Deputy Director, Cooperative Research Programs, and Manager, National Cooperative Highway Research Program
David Jared, Senior Program Officer
Mazen Alsharif, Senior Program Assistant
Natalie Barnes, Director of Publications
Heather DiAngelis, Associate Director of Publications
Jennifer Correro, Assistant Editor
NCHRP PROJECT 08-135 PANEL
Field of Transportation Planning—Area of Planning Methods & Processes
Michael J. Iacono, Minnesota Department of Transportation, St. Paul, MN (Chair)
Mei Chen, Kentucky Transportation Center, Lexington, KY
Dan J. Cook, HDR, Des Moines, IA
Marlene Vivian Delgadillo Canizares, Georgia Department of Transportation, Atlanta, GA
Philip B. Demosthenes, Philip B. Demosthenes, LLC, Denver, CO
Jeremy R. Jewkes, Washington State Department of Transportation, Olympia, WA
Camden V. Palvino, Apex Design, Denver, CO
Eugene Robert Russell, Sr., Kansas State University, Manhattan, KS
Taylor Sisson, Vermont Agency of Transportation, Barre, VT
Chung Trong Tran, FHWA Liaison
ACKNOWLEDGMENTS
The research team would like to thank the following individuals for their contributions to the successful completion of this project: Brian Dunn, Oregon Department of Transportation (retired); Jessie Jones, Arkansas Department of Transportation; Ryan Kenis, University of Florida graduate student; Emily Dang, University of Florida undergraduate student; Jonathan Crosby, University of Florida undergraduate student; Santiago Linares-Ramirez, Technical University of Munich graduate student; Yangqian Cai, Technical University of Munich doctoral student; Azhagan Avr, Transportation Data Analyst, Kittelson & Associates, Inc.; Dr. Nagui Rouphail, Senior Engineer, Kittelson & Associates, Inc.; and Dr. Rick Dowling, Senior Engineer, Kittelson & Associates, Inc.
Table of Contents
Appendix A: Literature Review and Current Practices
Appendix B: Two-Lane Highway Passing Lane Segment vs Multilane Highway Segment
Appendix C: Arterial Signal Spacing for Coordination
Appendix D: Intersection Influence Area
Appendix E: Highway Facility LOS Calculation
Appendix F: Bicycle Quality of Service on Rural Highways, Survey of Practitioners
Appendix G: Bicycle Quality of Service on Rural Highways, Survey of Bicyclists
NCHRP Web-Only Document 392 contains the conduct of research report for NCHRP Project 08-135 and accompanies NCHRP Research Report 1102: Reliability and Quality of Service Evaluation Methods for Rural Highways: A Guide. Readers can read or purchase NCHRP Research Report 1102 on the National Academies Press website (nap.nationalacademies.org).
List of Figures
Figure A-1. Example vehicle trajectory through signalized intersection influence area
Figure A-2. Example vehicle speed profile through signalized intersection influence area
Figure A-3. NCHRP 3-100: Example Speed Profile for Rural Corridor (SR 539 NB, Whatcom County, WA)
Figure A-5. Speed calculation for facility-level analysis
Figure B-1. Multilane Highway Segment Speed-Flow Curves Plot
Figure B-2. Passing Lane Segment Speed-Flow Curve Plot
Figure B-4. Multilane vs Two-lane 0.5 Mile 0% Grade Speed Flow Curves Plot
Figure B-5. Multilane vs Two-lane 0.5 Mile 2% Grade Speed Flow Curves Plot
Figure B-6. Multilane vs Two-lane 0.5 Mile 4% Grade Speed Flow Curves Plot
Figure B-7. Multilane vs Two-lane 0.5 Mile 6% Grade Speed Flow Curves Plot
Figure B-8. Multilane vs Two-lane 1.5 Mile 0% Grade Speed Flow Curves Plot
Figure B-9. Multilane vs Two-lane 1.5 Mile 2% Grade Speed Flow Curves Plot
Figure B-10. Multilane vs Two-lane 1.5 Mile 4% Grade Speed Flow Curves Plot
Figure B-11. Multilane vs Two-lane 1.5 Mile 6% Grade Speed Flow Curves Plot
Figure B-12. Multilane vs Two-lane 2.5 Mile 0% Grade Speed Flow Curves Plot
Figure B-13. Multilane vs Two-lane 2.5 Mile 2% Grade Speed Flow Curves Plot
Figure B-14. Multilane vs Two-lane 2.5 Mile 4% Grade Speed Flow Curves Plot
Figure B-15. Multilane vs Two-lane 2.5 Mile 6% Grade Speed Flow Curves Plot
Figure C-1. Signal spacing associated with effectively isolated operation
Figure C-2. Example of relationship between PVG, cycle length, and intersection spacing
Figure D-1. Four intersection locations along rural highways in Central Florida
Figure D-2. Yeehaw Junction Site (map view)
Figure D-3. Yeehaw Junction Site (State Road 60 – East to West Corridor, High % of heavy vehicles)
Figure D-4. Bronson Memorial Hwy and Arthur Gallagher Blvd Site (map view)
Figure D-6. SR-520 and Maxim Parkway Site (map view)
Figure D-7. SR-520 and Maxim Parkway Site (Upstream Eastbound, closer to intersection)
Figure D-8. FL-46 and CR-426/1st Street Site (map view)
Figure D-9. FL-46 and CR-426/1st Street Site (CR-426, northbound direction, closer to intersection)
Figure D-10. Seven Stop controlled intersections in Florida
Figure D-11. Lake Pickett Road at N Fort Christmas Road, FL
Figure D-12. Lake Pickett Road at N Fort Christmas Road, FL (satellite view)
Figure D-13. Taylor Creek Road at E Colonial Drive, FL
Figure D-14. Taylor Creek Road at E Colonial Drive, FL (satellite view)
Figure D-15. S Fort Christmas Road at E Colonial Drive, FL
Figure D-16. S Fort Christmas Road at E Colonial Drive, FL (satellite view)
Figure D-18.Taylor Creek Road at FL-520 (Street View)
Figure D-19. Deer Park Road at Nova Road
Figure D-20. Deer Park Road at Nova Road (Street View)
Figure D-21. Nova Road at E. Irlo Bronson Memorial Hwy, FL
Figure D-22. Nova Road at E. Irlo Bronson Memorial Hwy, FL (satellite view)
Figure D-23. Holopaw Road (US-441 S) at E. Irlo Bronson Memorial Hwy, FL
Figure D-24. Holopaw Road (US-441 S) at E. Irlo Bronson Memorial Hwy, FL (satellite view)
Figure D-25. SR-539 in Whatcom County, Washington (Map View)
Figure D-26. SR-539 in Whatcom County, Washington (satellite view)
Figure D-27. Borgen Boulevard in Gig Harbor, Washington (Map View)
Figure D-28. Borgen Boulevard in Gig Harbor, Washington (satellite view)
Figure D-29. Golden Road in Golden, Colorado (Map View)
Figure D-30. Golden Road in Golden, Colorado (satellite view)
Figure D-31. Steps to pre-process GPS data
Figure D-32. Data filtering criteria
Figure D-33. Speed profiles along FL-46 (3000 ft upstream & downstream) (speed in km/h on Y-axis)
Figure D-34. Sample trajectory, step 1
Figure D-35. Sample trajectory, step 2
Figure D-36. Sample trajectory, step 3
Figure D-37. Sample trajectory, step 4
Figure D-38. Sample trajectory, step 5
Figure D-39. Speed vs distance plot
Figure D-40. Speed vs distance plot for step 3
Figure D-41. Speed vs distance plot for step 4
Figure D-42. Upstream influence area lengths of three types of intersection
Figure D-43. Average speed reduction at different percentile distances
Figure D-44. Average percentage speed reduction at percentiles distances
Figure D-47. Upstream and downstream influence areas of signalized intersection
Figure D-48. Upstream and downstream influence areas of roundabout intersection
Figure D-49. Upstream and downstream influence areas of stop control intersection
Figure E-6. LOS score versus service measure value for two-lane highway segments
Figure E-7. LOS adjustment factor (α)
Figure F-1. Number of responses per state
Figure F-2. Descriptive analysis – commute cycling experience
Figure F-3. Descriptive analysis – leisure cycling experience
Figure F-4. Reasons to use selected method
Figure F-6. Use of methodologies by state DOTs
Figure F-7. Ranking of elements
Figure F-8. Characteristics to define bicycle design users for rural highways
Figure G-2. Survey section: user segmentation
Figure G-3. Survey instructions
Figure G-4. Example of choice task
Figure G-6. Example of bicycle infrastructure
Figure G-7. Number of responses by state
Figure G-8. Number of responses per million inhabitants by state
Figure G-9. Classification of cyclists by Felix et al. (2009)
Figure G-10. Relative importance when cycling for rural cyclists
Figure G-11. Scenario: Path or trail
Figure G-12. Comfort levels for path or trail
Figure G-13. Comfort levels for bike lane on two-lane street
Figure G-14. Comfort levels for bike lane on major street with four lanes
Figure G-15. Comfort levels for striped bike lane on two-lane street
Figure G-17. Comfort levels for striped bike lane on four-lane street
Figure G-18. Comfort levels for no bike lane on two-lane street
Figure G-20. Comfort levels for striped bike lane on major street with four lanes
Figure G-21. Comfort level by stated cyclist type
Figure G-22. Comfort level by seasonal cycling frequency
List of Tables
Table B-1. Geometric Characteristics Experimental Design Settings
Table B-2. Traffic Characteristics Experimental Design Settings
Table C-1. Urban Street Determination Experimental Design
Table D-1. Total number of study sites with attributes
Table D-2. Roundabout sites attributes
Table D-3. Upstream influence area results for signalized intersection
Table D-4. Downstream influence area results for signalized intersection
Table D-5. Upstream influence area results for stop controlled intersection
Table D-6. Downstream influence area results for stop-controlled intersections
Table D-7. Upstream influence area results for roundabout intersections
Table D-8. Downstream influence area results for roundabout intersections
Table E-1. LOS Constancy Example Calculations
Table E-2. LOS Constancy Adjustment Value
Table F-1. Number of responses by the last page of the survey
Table F-2. Descriptive analysis – agency
Table F-3. Descriptive analysis – department
Table F-4. Descriptive analysis – position
Table F-5. Descriptive analysis – agency perform work for
Table F-6. Cycling experience of respondents
Table F-7. Number of responses by the last page of the survey
Table F-9. Other methodologies applied
Table F-11. Main concerns regarding bicycle indicators – all responses
Table F-12. Methods applied – state DOT responses
Table F-13. Main concerns regarding bicycle indicators – state DOT responses
Table F-14. Comparison across variables for shared and bicycle lanes
Table F-15. Ranking of elements – statistics summary
Table F-16. Ranked variables by cycling experience
Table F-17. Ranked variables by applied methodology
Table F-18. Bicyclist attributes -statistics summary
Table F-19. Bicyclist attributes by cycling experience of the respondent
Table F-20. Comments to bicyclist attributes. Attributes that should be considered
Table F-21. Comments to bicyclist attributes. Attributes that should not be considered?
Table G-1. Attributes and attributes level of the choice tasks
Table G-2. Attributes of the choice task scenarios
Table G-3. Number of responses by the last section of the survey
Table G-4. Country of residence
Table G-5. Survey descriptive statistics - gender
Table G-6. Survey descriptive statistics – age
Table G-7. Survey descriptive statistics – household income
Table G-8. Survey descriptive statistics – main commute mode
Table G-10. Cyclist type by seasonal cycling frequency
Table G-11. Cyclist type by seasonal cycling frequency – gender
Table G-12. Cyclist type by seasonal cycling frequency – age
Table G-13. Cyclist type by seasonal cycling frequency – main commute mode
Table G-14. Cyclist type by seasonal cycling frequency – frequency
Table G-15. Cyclist type by seasonal cycling frequency – seasons
Table G-16. Cyclist type by seasonal cycling frequency – day of week and time period
Table G-17. Cyclist type by seasonal cycling frequency – weather conditions
Table G-18. Stated cyclist type - distribution
Table G-19. Stated cyclist type – gender
Table G-22. Stated cyclist type – frequency
Table G-23. Stated cyclist type – seasons
Table G-24. Stated cyclist type – day of week and time period
Table G-25. Stated cyclist type – frequency
Table G-26. Comparison between cycling frequency and stated cyclist type
Table G-27. Percentage of times selected by speed limit
Table G-28. Percentage of times selected by grade
Table G-29. Percentage of times selected by automobile traffic volume
Table G-30. Percentage of times selected by presence of shoulder and shoulder width
Table G-31. Percentage of times selected by pavement quality
Table G-32. Percentage of times selected by context classification
Table G-33. Percentage of times selected by scenario
Table G-34. Choice model – statistical summary
Table G-35. Ranking – summary of statistics
Table G-36. Ranking model – statistics summary
