Strategies to Address
Utility Issues During
Highway Construction
Cesar Quiroga
Jenny Naranjo
Harshit Shukla
Texas A&M Transportation Institute
College Station, TX
Jesse Cooper
HDR Engineering, Inc.
Austin, TX
Conduct of Research Report for NCHRP Project 15-69
Submitted October 2023
NCHRP
Web-Only Document 396
Strategies to Address Utility Issues During Highway Construction
Cesar Quiroga
Jenny Naranjo
Harshit Shukla
Texas A&M Transportation Institute
College Station, TX
Jesse Cooper
Hdr Engineering, Inc.
Austin, TX
Conduct of Research Report for NCHRP Project 15-69
Submitted October 2023
© 2023 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.
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.
COPYRIGHT INFORMATION
Authors herein are responsible for the authenticity of their materials and for obtaining written permissions from publishers or persons who own the copyright to any previously published or copyrighted material used herein.
Cooperative Research Programs (CRP) grants permission to reproduce material in this publication for classroom and not-for-profit purposes. Permission is given with the understanding that none of the material will be used to imply TRB, AASHTO, APTA, FAA, FHWA, FTA, GHSA, or NHTSA endorsement of a particular product, method, or practice. It is expected that those reproducing the material in this document for educational and not-for-profit uses will give appropriate acknowledgment of the source of any reprinted or reproduced material. For other uses of the material, request permission from CRP.
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.
The Transportation Research Board, the National Academies, and the sponsors of the National Cooperative Highway Research Program do not endorse products or manufacturers. Trade or manufacturers’ names appear herein solely because they are considered essential to the object of the report.
The information contained in this document was taken directly from the submission of the author(s). This material has not been edited by TRB.
The National Academy of Sciences was established in 1863 by an Act of Congress, signed by President Lincoln, as a private, nongovernmental institution to advise the nation on issues related to science and technology. Members are elected by their peers for outstanding contributions to research. Dr. Marcia McNutt is president.
The National Academy of Engineering was established in 1964 under the charter of the National Academy of Sciences to bring the practices of engineering to advising the nation. Members are elected by their peers for extraordinary contributions to engineering. Dr. John L. Anderson is president.
The National Academy of Medicine (formerly the Institute of Medicine) was established in 1970 under the charter of the National Academy of Sciences to advise the nation on medical and health issues. Members are elected by their peers for distinguished contributions to medicine and health. Dr. Victor J. Dzau is president.
The three Academies work together as the National Academies of Sciences, Engineering, and Medicine to provide independent, objective analysis and advice to the nation and conduct other activities to solve complex problems and inform public policy decisions. The National Academies also encourage education and research, recognize outstanding contributions to knowledge, and increase public understanding in matters of science, engineering, and medicine.
Learn more about the National Academies of Sciences, Engineering, and Medicine at www.nationalacademies.org.
The Transportation Research Board is one of seven major program divisions of the National Academies of Sciences, Engineering, and Medicine. The mission of the Transportation Research Board is to mobilize expertise, experience, and knowledge to anticipate and solve complex transportation-related challenges. The Board’s varied activities annually engage about 8,500 engineers, scientists, and other transportation researchers and practitioners from the public and private sectors and academia, all of whom contribute their expertise in the public interest. The program is supported by state transportation departments, federal agencies including the component administrations of the U.S. Department of Transportation, and other organizations and individuals interested in the development of transportation.
Learn more about the Transportation Research Board at www.TRB.org.
COOPERATIVE RESEARCH PROGRAMS
CRP STAFF FOR NCHRP WEB-ONLY DOCUMENT 396
Waseem Dekelbab, Deputy Director, Cooperative Research Programs, and Manager, National Cooperative Highway Research Program
Camille Crichton-Sumners, 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 15-69 PANEL
Field of Design—Area of General Design
Larry Ditty, Jr., Pennsylvania Department of Transportation, Harrisburg, PA (Chair)
Gregory W. Faber, Texas Department of Transportation, Austin, TX
JoAnn D. Kurts, Louisiana Department of Transportation and Development, Baton Rouge, LA
James E. Moore, II, University of Southern California, Los Angeles, CA
Kevin C. Payne, Johnson, Mirmiran & Thompson, Hunt Valley, MD
Mario Benito Rojas, Choice Engineering Consultants, Inc., Miami, FL
Casey Soneira, AASHTO, Washington, DC
Gorette Yung, Michigan Department of Transportation, Southfield, MI
Julie A. Johnston, FHWA Liaison
ACKNOWLEDGMENTS
The research reported herein was performed under NCHRP Project 15-69 by the Texas A&M Transportation Institute (TTI) in collaboration with HDR Engineering, Inc. TTI was the prime contractor for this study, with Sponsored Research Services at the Texas A&M University System serving as Fiscal Administrator.
Cesar Quiroga, Ph.D., P.E., Senior Research Engineer and Manager of the Utility Engineering Program at TTI, was the Principal Investigator. The other authors of this report are Jenny Naranjo, Assistant Research Scientist in the Utility Engineering Program at TTI; Harshit Shukla, Ph.D., Assistant Research Scientist in the Utility Engineering Program at TTI; and Jesse Cooper, RPLS, Senior Utility Manager at HDR Engineering, Inc.
The authors are grateful for the invaluable assistance provided by officials at departments of transportation, consulting companies, and utility owners throughout the country, who took part in the practitioner survey, participated in multiple discussions with the research team, provided change order data and materials for case studies, and clarified or expanded concepts. The research would not have been possible without their help.
TABLE OF CONTENTS
CAUSES OF UTILITY ISSUES DURING CONSTRUCTION
FUNCTIONAL REQUIREMENTS FOR A DECISION SUPPORT SYSTEM
PROCEDURES FOR CONDUCTING UTILITY INSPECTIONS
Recommendations Prior to Letting
Recommendations During Construction
UTILITY-RELATED IMPACTS ON PROJECT DELIVERY
USE OF UTILITY IMPACT ASSESSMENT TOOLS DURING PROJECT DELIVERY
Assessment and Management of Utility Risks
Utility Investigations and Impact Analysis
CONSTRUCTION AND UTILITY INSPECTION PRACTICES
Markers and Radio Frequency Identification
Utility Data Available during Construction
Structure-from-Motion Photogrammetry
Smartphones and SfM Processing
Light Detection and Ranging (LiDAR)
New Relevant Research Projects
CHAPTER 3. PRACTITIONER SURVEY RESULTS
BASIC INFORMATION ABOUT RESPONDENTS
CAUSES OF PROJECT DELAYS AND COST INCREASES
Impact of Type of Utility Relocation
UTILITY-RELATED TIME EXTENSIONS, CHANGE ORDERS, AND CLAIMS
Tools Project Owners Use to Address Utility-Related Delays and Costs
Contractor Strategies to Address Utility Issues During Construction
Access to Change Order and Claim Databases
COLORADO—SH 82 BRIDGE RECONSTRUCTION AND NEW PEDESTRIAN BRIDGE CONSTRUCTION
TEXAS—US 281 WIDENING TO 6-LANE FREEWAY WITH 2-LANE DIRECTIONAL FRONTAGE ROADS
VIRGINIA—HILLSBORO IMPROVEMENT PROJECT
CHAPTER 5. CHANGE ORDER ANALYSIS
METHODOLOGY TO CLASSIFY UTILITY-RELATED CHANGE ORDERS
Disaggregated Reasons for UR Change Orders
CHAPTER 6. CHANGE ORDER CLASSIFICATION USING AI
DISCLOSURE ON THE USE OF ARTIFICIAL INTELLIGENCE
USING AI MODELS TO ASSIST WITH MANUAL REVIEW OF CHANGE ORDERS
CHAPTER 7. REQUIREMENTS FOR A DECISION SUPPORT SYSTEM
QUALITY OF CHANGE ORDER DESCRIPTIONS
System Components and Mockup User Interface
CHAPTER 8. UTILITY INSPECTION PROCEDURES
Case 1: Project Survey Control Point Verification
CHAPTER 9. CONCLUSIONS AND RECOMMENDATIONS
Causes of Utility Issues During Construction
Functional Requirements for a Decision Support System
Procedures for Conducting Utility Inspections
Recommendations Prior to Letting
Recommendations During Construction
ABBREVIATIONS, ACRONYMS, INITIALISMS, AND SYMBOLS
PART 3 – UTILITY-RELATED TIME EXTENSIONS, CHANGE ORDERS, AND CLAIMS
PART 4 – POTENTIAL CASE STUDIES
PART 5 – ADDITIONAL INFORMATION AND FOLLOW-UP
APPENDIX B. FUNDAMENTAL ARTIFICIAL INTELLIGENCE CONCEPTS
SUPERVISED AND UNSUPERVISED CLASSIFICATION
Multi-Layer Perceptron Classifier
NCHR Web-Only Document 396 contains the conduct of research report for NCHRP Project 15-69 and accompanies NCHRP Research Report 1110: Minimizing Utility Issues During Construction: A Guide. Readers can read or purchase NCHRP Research Report 1110 on the National Academies Press website (nap.nationalacademies.org).
LIST OF FIGURES
Figure 1. Risk Management Process Steps
Figure 2. Risk Register Matrix (Adapted from [23])
Figure 3. Test Pit to Expose Underground Utility Facilities
Figure 4. Mass Excavation to Expose Underground Utility Facilities During Construction
Figure 6. Sample Thrust Block Providing Structural Support to Pressure Pipelines
Figure 7. Image of 3D Textured Mesh Resulting from Densified 3D Point Cloud (101)
Figure 8. 3D Model Resulting from Using a Smartphone and SfM Photogrammetry Software
Figure 10. Type of Organization
Figure 11. Affiliation of Respondents within their Organization
Figure 12. Respondent Involvement in the Project Delivery Process
Figure 13. Respondent’s Role in the Project Delivery Process
Figure 14. Tools Highway Contractors Use to Address Utility-Related Delays and Costs
Figure 15. Scatterplot of Average Ratings and Standard Deviations
Figure 16. Grand Avenue Bridge Project in Glenwood Springs, Colorado
Figure 17. Utility Engineering Project Lifecycle (adapted from [106])
Figure 18. US 281 Highway Widening Project
Figure 19. Utility Conflict Locations on Working Project Files
Figure 20. Utility Conflict List Template – Spreadsheet No. 1 (Utility Conflicts)
Figure 22. Overhead Transmission Line in Conflict with Highway Overpass
Figure 23. Issue with Water Main Tie-In Location
Figure 24. Boring under Existing Gas Station Driveway
Figure 25. Sanitary Sewer Crossing
Figure 26. ReThink9 Project in Hillsboro, Virginia
Figure 27. Hillsboro, Virginia, after Project Completion
Figure 28. Change Order Dataset Used for AI Model Training, Testing, and Validation
Figure 29. Average UR Accuracy of AI Models for Validation Datasets
Figure 30. Training Time of AI models
Figure 31. Comparison of UR Accuracy of AI Models Among Six Cases
Figure 32. Distribution of UR and NUR Records by Composite Score
Figure 33. Macro for Highlighting Key Words in Microsoft® Excel®
Figure 34. Change Order Descriptions with Colorized Words
Figure 35. Main Components of the Cloud-Based IDSS
Figure 36. Mockup IDSS User Interface—Home Page
Figure 37. Mockup IDSS User Interface—Data Processing Page
Figure 38. Mockup IDSS User Interface—Reports Page
Figure 39. Mockup IDSS User Interface—System Management Page
Figure 42. Percentage of UR Change Order Records by Year
Figure 43. IDSS User Interface using Sample Change Order Records—Home Page
Figure 44. Project Survey Control Points
Figure 45. Planned versus Actual Locations—Sanitary Sewer Manhole
Figure 46. Planned versus Actual Locations—Water Line
Figure 47. Planned versus Actual Locations—Vault
Figure 48. 3D Model of Utility Features Using Photogrammetry and GCPs
LIST OF TABLES
Table 1. DOT Reasons for Delays in Utility Relocations
Table 2. Potential Causes of Project Delays Included in the 2002 Survey (2)
Table 3. Ranking of Top Ten Causes of Project Delays Based on Survey Results (2)
Table 4. Codes or Groupings of Change Orders (10)
Table 5. Change Order Categories and Reason Codes at TxDOT (12)
Table 6. Contractor Claim Categories at TxDOT
Table 7. Example Approaches for Probability Levels (23)
Table 8. Example Approaches for Impact Levels (23)
Table 9. Suggested Risks in FHWA’s Risk Register Management Tool (23)
Table 10. Comparison of Underground Detection Technologies (Adapted from [30])
Table 11. PennDOT’s Utility Impact Scores (33)
Table 12. WSDOT’s SUE Quality Level Requirements (38)
Table 13. Agencies that Received Funds to Implement the R01A, R01B, and R15B Products
Table 14. Top Five Decision Drivers (43)
Table 15. Survey Accuracy Requirements (48)
Table 16. Survey Spacing Requirements as a Function of Curve Radius (48)
Table 17. Construction Survey Task List (49)
Table 18. Minimum Horizontal and Vertical Tolerances for Highway Features (55)
Table 19. Control and Survey Tolerances (61)
Table 20. Construction Survey Tolerances (68)
Table 21. Critical Elements Bridge Elements (69)
Table 22. Construction Survey Tolerances (72)
Table 23. Accuracy Error Allowances for Design Surveys (86)
Table 24. Commonly Used Utility Facility Markers (29)
Table 25. Symbology for Average Ratings and Standard Deviations
Table 26. Risk Factors – Project Planning and Design (Aggregated Average)
Table 27. Risk Factors – Project Planning and Design (Disaggregated Average)
Table 28. Risk Factors – Highway Construction (Aggregated Average)
Table 29. Risk Factors – Highway Construction (Disaggregated Average)
Table 30. Risk Factors – Environmental Process (Aggregated Average)
Table 31. Risk Factors – Environmental Process (Disaggregated Average)
Table 32. Risk Factors – Right-of-Way Acquisition (Aggregated Average)
Table 33. Risk Factors – Right-of-Way Acquisition (Disaggregated Average)
Table 34. Risk Factors – Utility Process (Aggregated Average)
Table 35. Risk Factors – Utility Process (Disaggregated Average)
Table 36. Impact of Type of Utility Relocation on Project Delivery Delays (Average)
Table 37. Risk Factors Causing Unknown Costs to Contractors (Average)
Table 39. Top 20 Risk Factors (Aggregated Average)
Table 40. Top 20 Risk Factors (Disaggregated Average)
Table 42. Change Order and Claim Data Received from State DOTs
Table 43. Commonly Used One-Word and Two-Word UR Terms
Table 44. Disaggregated List of Reasons for UR Change Orders
Table 45. Case 1: Reasons for UR Change Orders
Table 46. Case1: Most Frequent UR Change Order Terms
Table 47. Case 2: UR Change Order Classification
Table 48. Case 2: Disaggregated Reasons for UR Change Orders
Table 49. Case 2: Strongest UR Change Orders Predictors
Table 50. Case 5: Reasons for UR Change Orders
Table 51. Case 5: Strongest UR Change Orders Predictors
Table 52. Case 6: Reasons for UR Supplemental Agreements
Table 53. Case 6: Reasons for UR Claims
Table 54. Case 6: Reasons for Combined UR Supplemental Agreements and Claims
Table 55. Case 6: Strongest UR Supplemental Agreement Predictors
Table 56. Case 8: Reasons for UR Change Orders
Table 57. Case 8: Most Frequent UR Change Order Terms
Table 58. Case 9: Reasons for UR Change Orders
Table 59. Case 9: Strongest UR Change Orders Predictors
Table 60. Percentage of UR Change Orders per Disaggregated Change Order Reason
Table 61. Word Count Before and After Text Preprocessing
Table 62. Configuration of AI Models and Vectorization Techniques
Table 63. Results of AI Models on Change Order Datasets
Table 64. Coordinates of Control Point F 1465 (Point ID AY1684)
Table 65. Top 20 Utility-Related Risk Factors by Stakeholder Group
Table 66. Required Elements and Elements that Enhance the Quality of Utility Information