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Data-Driven Pavement Maintenance and Rehabilitation Strategies for GDOT's New State Route Prioritization Policy

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Data-Driven Pavement Maintenance and Rehabilitation Strategies for GDOT's New State Route Prioritization Policy GEORGIA DOT RESEARCH PROJECT 16-37 Final Report DATA-DRIVEN PAVEMENT MAINTENANCE AND REHABILITATION STRATEGIES FOR GDOT’S NEW STATE ROUTE PRIORITIZATION POLICY Office of Performance-based Management and Research 600 West Peachtree St. NW | Atlanta, GA 30308 1.Report No.: 2. Government Accession 3. Recipient's Catalog No.: N/A FHWA-GA-19-1637 No.: N/A 4. Title and Subtitle: 5. Report Date: April 2019 Data-Driven Pavement Maintenance and Rehabilitation Strategies for GDOT’s New State Route Prioritization Policy 6. Performing Organization Code: N/A 7. Author(s): Yichang (James) Tsai, Ph.D.; Zhaohua Wang, 8. Performing Organ. Report No.: Ph.D.; Lauren Gardner; Ryan Salameh; Yi Jiao 16-37 9. Performing Organization Name and Address: 10. Work Unit No.: Georgia Institute of Technology 790 Atlantic Drive 11. Contract or Grant No.: Atlanta, GA 30332-0355 PI# 0015380 12. Sponsoring Agency Name and Address: 13. Type of Report and Period Georgia Department of Transportation Covered: Office of Performance-based Management and Research Final; December 2016 – April 600 West Peachtree St. NW 2019 Atlanta, GA, 30308 14. Sponsoring Agency Code: 15. Supplementary Notes: Prepared in cooperation with the U.S. Department of Transportation, Federal Highway Administration. 16. Abstract: The Georgia Department of Transportation (GDOT) has used the models and application that were developed through the RP 05-19 to justify and forecast the network-level, long-term pavement performance, and Maintenance, Rehabilitation, and Reconstruction (MR&R) need to the legislature. However, the Markov-chain-based pavement deterioration transition probabilities have not been updated for more than 10 years and do not reflect the most recent pavement deterioration behaviors. In addition, GDOT has established a new policy that categorizes state highways into four priority categories according to their importance and utilization: critical, high, medium, and low. To improve the accuracy and reliability of forecasting network-level pavement performance and predicting future MR&R needs in light of the new state route priority categories, this research project studied pavement deterioration behavior at both project and network levels, updated the pavement deterioration transition probabilities using the recent COPACES data, analyzed the treatment unit cost and Annual Average Escalation Rate (AAER), and conducted comprehensive what-if analysis using the new software application, GDOT LP&S. Conclusions and recommendations for future research were offered. 17. Key Words: Asphalt pavement; deterioration; state route priority 18. Distribution Statement: No category; maintenance, rehabilitation and reconstruction; Restriction Markov transition probability; optimization; what-if analysis 19. Security Classification (of 20. Security classification 21. Number of Pages: 22. Price: this report): Unclassified (of this page): Unclassified 180 Free Contract Research GDOT Research Project No. 16-37 Final Report DATA-DRIVEN PAVEMENT MAINTENANCE AND REHABILITATION STRATEGIES FOR GDOT’S NEW STATE ROUTE PRIORITIZATION POLICY By Yichang (James) Tsai, Ph.D., P.E. Zhaohua Wang, Ph.D., P.E. Lauren Gardner Ryan Salameh Yi Jiao Georgia Institute of Technology Contract with Georgia Department of Transportation In cooperation with U.S. Department of Transportation Federal Highway Administration April 2019 The contents of this report reflect the views of the author(s) who is (are) responsible for the facts and the accuracy of the data presented herein. The contents do not necessarily reflect the official views or policies of the Georgia Department of Transportation or of the Federal Highway Administration. This report does not constitute a standard, specification, or regulation. i ii TABLE OF CONTENTS LIST OF TABLES v LIST OF FIGURES vii ACRONYMS AND ABBREVIATIONS xi EXECUTIVE SUMMARY 1 CHAPTER 1. INTRODUCTION 4 RESEARCH BACKGROUND AND RESEARCH NEED .....................................................4 RESEARCH OBJECTIVES .....................................................................................................5 REPORT ORGANIZATION ....................................................................................................5 CHAPTER 2. LITERATURE REVIEW 7 PAVEMENT CONDITION DATA COLLECTION ...............................................................8 OTHER DATA SOURCES FOR PAVEMENT MANAGEMENT DATABASES ..............15 ORGANIZATION OF NETWORK-LEVEL PAVEMENT DATA ......................................17 PAVEMENT DETERIORATION MODELING ...................................................................24 SUMMARY ............................................................................................................................31 CHAPTER 3. PROJECT-LEVEL DETERIORATION MODELING 32 INTRODUCTION ..................................................................................................................32 DATA PREPROCESSING .....................................................................................................35 DEVELOPMENT OF BAYESIAN MODEL ........................................................................35 MODEL APPLICATION FOR USING COPACES DATA ..................................................45 iii FAMILY-LEVEL DATA ANALYSIS ..................................................................................58 SUMMARY ............................................................................................................................63 CHAPTER 4. NETWORK-LEVEL PAVEMENT DETERIORATION MODELING AND VALIDATION 65 DEVELOPMENT OF A NETWORK-LEVEL PMS MODEL FOR GEORGIA ..................65 SUMMARY ............................................................................................................................85 CHAPTER 5. MULTI-YEAR PAVEMENT PERFORMANCE AND MR&R NEEDS 87 FEDERAL-LEVEL FUNDING AND PERFORMANCE CRITERIA FOR MR&R ............87 STATE-LEVEL FUNDING AND PERFORMANCE CRITERIA FOR MR&R ..................90 ANALYSIS OF PERFORMANCE FORECASTING AND FUNDING NEEDS .................92 SUMMARY ..........................................................................................................................109 CHAPTER 6. CONCLUSIONS AND RECOMMENDATIONS 111 ACKNOWLEDGMENTS 114 REFERENCES 115 Appendix I: User’s Guide for GDOT LP&S 122 Appendix II: Markov Chain Transition Probability Matrices (TPMS) 158 Appendix III: Linear Programming Model Formulations 164 iv LIST OF TABLES Table 2-1. PACES distress information. ................................................................................ 14 Table 2-2. Project rating categories. ...................................................................................... 17 Table 2-3. Characteristics of state route priority categories (Wiegand & Susten, 2016). 23 Table 3-1. Summary of posterior distribution of α,β,ρ,κ,η. ................................................. 53 Table 3-2. COPACES data of ‘Project 001101210015.825.6’. ............................................. 56 Table 3-3. Summary of posterior distribution of α,β,ρ,κ,η. ................................................. 57 Table 3-4. Summary of mean value of α,β,ρ,κ,η,α/ρ (District 5). ........................................ 60 Table 4-1. Non-interstate highway pavement condition from FY2010 – FY 2015............. 69 Table 4-2. Interstate highway pavement condition from FY2010 – FY 2015..................... 69 Table 4-3. Notation of markov TPM. ..................................................................................... 70 Table 4-4. TPM for critical, non-interstate families for seven working districts. .............. 72 Table 4-5. Treatment for each condition state. ..................................................................... 73 Table 4-6. Major preventative maintenance unit cost. ......................................................... 75 Table 4-7. Average number of COPACES project survey miles. ........................................ 76 Table 4-8. Minor preventative maintenance unit cost. ......................................................... 77 Table 4-9. Final unit costs for model. ..................................................................................... 79 v Table 4-10. Treatment effect on pavement condition. .......................................................... 79 Table 4-11. Difference between model simulated results and historical condition. ........... 83 Table 5-1. Minimum composite score criteria for priority categories. ............................. 102 Table 5-2. Sensitivity study budget variation. ..................................................................... 105 vi LIST OF FIGURES Figure 2-1. Illustration. PACES survey sampling terminology. .......................................... 13 Figure 2-2. Chart. State of pavement network in Georgia for FY 2015. ............................ 18 Figure 2-3. Map. GDOT working districts (GDOT, 2014b). ............................................... 20 Figure 2-4. Map. Soil differences in the state of Georgia (UGA, 2017). ............................. 21 Figure 2-5. Map. Interstate versus non-interstate routes in Georgia. ................................. 22 Figure 2-6. Map. State route prioritization categories. ........................................................ 24 Figure 3-1. Graph. Rate deduction curve (Park et al., 2008). .............................................. 36 Figure 3-2. Chart. Data processing flow. ............................................................................... 46 Figure 3-3.
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