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

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

LIST OF FIGURES

LIST OF TABLES

SUMMARY

CAUSES OF UTILITY ISSUES DURING CONSTRUCTION

Literature Review

Practitioner Survey

Change Order Analysis

CASE STUDIES

FUNCTIONAL REQUIREMENTS FOR A DECISION SUPPORT SYSTEM

PROCEDURES FOR CONDUCTING UTILITY INSPECTIONS

RECOMMENDATIONS

Recommendations Prior to Letting

Recommendations During Construction

SUGGESTED RESEARCH

CHAPTER 1. INTRODUCTION

CHAPTER 2. LITERATURE REVIEW

INTRODUCTION

UTILITY-RELATED IMPACTS ON PROJECT DELIVERY

Impacts on Project Delays

Impacts on Project Costs

Impacts to Contractors

USE OF UTILITY IMPACT ASSESSMENT TOOLS DURING PROJECT DELIVERY

Assessment and Management of Utility Risks

Utility Investigations and Impact Analysis

Utility Conflict Management

Decision Support Systems

CONSTRUCTION AND UTILITY INSPECTION REQUIREMENTS

Alabama

Alaska

Arizona

Arkansas

California

Colorado

Connecticut

Georgia

Idaho

Illinois

Iowa

Kansas

Massachusetts

Michigan

Minnesota

New Jersey

New Mexico

North Carolina

North Dakota

Oregon

Pennsylvania

South Carolina

Texas

Utah

Vermont

Virginia

Washington

West Virginia

Wisconsin

CONSTRUCTION AND UTILITY INSPECTION PRACTICES

Markers and Radio Frequency Identification

Utility Data Available during Construction

Unmanned Aircraft Systems

Structure-from-Motion Photogrammetry

Smartphones and SfM Processing

Light Detection and Ranging (LiDAR)

New Relevant Research Projects

CHAPTER 3. PRACTITIONER SURVEY RESULTS

INTRODUCTION

BASIC INFORMATION ABOUT RESPONDENTS

CAUSES OF PROJECT DELAYS AND COST INCREASES

Project Planning and Design

Highway Construction

Environmental Process

Right-of-way Acquisition

Utility Process

Impact of Type of Utility Relocation

Unknown Costs to Contractors

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

POTENTIAL CASE STUDIES

ADDITIONAL COMMENTS BY RESPONDENTS

STANDARD DEVIATIONS

OVERALL TRENDS

CHAPTER 4. CASE STUDIES

INTRODUCTION

COLORADO—SH 82 BRIDGE RECONSTRUCTION AND NEW PEDESTRIAN BRIDGE CONSTRUCTION

Project Overview

Management of Utilities

Change Orders

TEXAS—US 281 WIDENING TO 6-LANE FREEWAY WITH 2-LANE DIRECTIONAL FRONTAGE ROADS

Project Overview

Management of Utilities

Change Orders

VIRGINIA—HILLSBORO IMPROVEMENT PROJECT

Project Overview

Management of Utilities

Use of RFID Markers

Change Orders

CHAPTER 5. CHANGE ORDER ANALYSIS

INTRODUCTION

METHODOLOGY TO CLASSIFY UTILITY-RELATED CHANGE ORDERS

Commonly Used UR Terms

Disaggregated Reasons for UR Change Orders

CASE 1

CASE 2

CASE 5

CASE 6

CASE 8

CASE 9

GENERAL TRENDS

CHAPTER 6. CHANGE ORDER CLASSIFICATION USING AI

INTRODUCTION

DISCLOSURE ON THE USE OF ARTIFICIAL INTELLIGENCE

METHODOLOGY

Dataset Selection

Preprocessing

Vectorization

Training

Testing and Validation

RESULTS AND DISCUSSION

USING AI MODELS TO ASSIST WITH MANUAL REVIEW OF CHANGE ORDERS

CHAPTER 7. REQUIREMENTS FOR A DECISION SUPPORT SYSTEM

INTRODUCTION

QUALITY OF CHANGE ORDER DESCRIPTIONS

SYSTEM REQUIREMENTS

System Components and Mockup User Interface

IDSS Functions

CHAPTER 8. UTILITY INSPECTION PROCEDURES

DATA COLLECTION EQUIPMENT

Unmanned Aircraft Systems

Mobile Devices

DATA COLLECTION SOFTWARE

BENCHMARK TESTS

DATA COLLECTION PROTOCOLS

Case 1: Project Survey Control Point Verification

Case 2: Point Features

Case 3: Line Features

Case 4: Polygon Features

Case 5: 3D Objects

CHAPTER 9. CONCLUSIONS AND RECOMMENDATIONS

CONCLUSIONS

Causes of Utility Issues During Construction

Utility Impact Analysis Tools

Case Studies

Functional Requirements for a Decision Support System

Procedures for Conducting Utility Inspections

RECOMMENDATIONS

Recommendations Prior to Letting

Recommendations During Construction

SUGGESTED RESEARCH

REFERENCES

ABBREVIATIONS, ACRONYMS, INITIALISMS, AND SYMBOLS

APPENDIX A. SURVEY QUESTIONS

PART 1 – BASIC INFORMATION

PART 2 – CAUSES OF PROJECT DELAYS AND COST INCREASES

Project Planning and Design

Highway Construction

Environmental Process

Right-of-Way Acquisition

Utility Process

Types of Utility Relocations

Unknown Costs to Contractors

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

INTRODUCTION

SUPERVISED AND UNSUPERVISED CLASSIFICATION

AI MODEL DEVELOPMENT PHASES

Preprocessing

Vectorization

Training

Testing

Deployment

ACTIVATION FUNCTION

AI MODELS

Logistic Regression

k-Nearest Neighbors

Multi-Layer Perceptron Classifier

Support Vector Machine

Random Forest

Deep Learning

VECTORIZATION

CountVectorizer

TF-IDF

BERT

GPT

PERFORMANCE METRICS

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 5. Utility Conflict Management Stages and Activities (Assuming a Design-Bid-Build Project Delivery Method)

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 9. Survey Response Map

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 21. Utility Conflict List Template – Spreadsheet No. 1 (Utility Conflict Resolution Alternatives)

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 40. Mockup Keyword Color Assignments

Figure 41. Number of UR Change Order Records by Year

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

Figure 49. Project-Level Risk Management Process

Figure 50. Confusion Matrix of True and Predicted Labels

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 38. Frequently Used Contractor Strategies to Address Utility Issues During Construction (Average)

Table 39. Top 20 Risk Factors (Aggregated Average)

Table 40. Top 20 Risk Factors (Disaggregated Average)

Table 41. Case Studies

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