NMDOT Pavement Management – Uses in Meeting Federal Requirements and Project Selection April 24 and 26, 2018 Shawn Romero, EI Jeff Mann, PE Pavement Management And Design Bureau
Overview – This Is What We are Talking About Generalized Pavement Condition Curve 2
Overview • Introduction to and History of Pavement Management (PMS db) (JSM) • What, When, How of NMDOT PMS db (JSM) • PMS db Data Collection Procedures (SR) • PMS db Data Collection QC/QA Procedures (SR) • PMS db (SR) – Projections, Scenarios, Budget, Project Selection • 23 CFR 490 Requirements and Discussion Points (JSM) 3
Introduction to and History of Pavement Management Systems and Database (PMS db) Who Knows When it Started • 1956-1960 AASHO Road Test • – Ottawa, Illinois – Pavement Serviceability Index (PSI) was born • Concept that “RIDE COMFORT” along w Safety were the performance objections of ALL PAVEMENTS 1970s • – Several Papers on Pavement Management – 1977 First Textbook “Pavement Management Systems” 4
Introduction to and History of Pavement Management Systems and Database (PMS db) 1986 (1993) AASHTO Guide for Design of Pavement Structures • – Chapter 2 Pertains to Network Level and Project Level Determination 23 CFR Part 626 (Non Regulatory) • Recommends that Pavement Design shall be used in conjunction with – performance and cost data from PMS db MAP 21, FAST Act, 23 CFR 490 • Transportation Asset Mgmt Plan (TAMP) – Require Minimum Standards for Operating PMS db for Interstates and NHS – We will discuss later – 5
Introduction to and History of Pavement Management Systems and Database (PMS db) • What is a PMS db? – From 2012, Second Ed “Pavement Management Guide” • “…provides a systematic approach to management a pavement network that enables agencies (NMDOT) to evaluate the consequences associated with various investment decisions ( THINK BUDGETS ) and to determine the most cost-effective use of available funds ( THINK PERFORMANCE )… • Network Level Data ie Performance of our Roadway System Reporting – FHWA HPMS, LFC, 23 CFR 490 – • Project Level Data Managed Section Data of Distress (2 Mile Sections) – NMDOT has ALL distress data for every 1/10 mile of across our network – 6
An Effective Pavement Management System db Should… Assess Current and Future Pavement Conditions • Network Level Considerations and Analyze – Performance Curves and Modeling – Estimate Funding Needs to Achieve a Desired Condition • Level Budgeting – State of Good Repair – Identify Preservation, Rehabilitation and Reconstruction • Projects that Optimize Funding Project Level Analyses – 7
An Effective Pavement Management System db Should…con’t Illustrate Consequences of Funding Levels on Condition • LFC, FHWA, TAMP Reporting – Performing Scenarios – Justify and Defend Funding Levels Compared to Performance – Reporting Methods • 8
Discussion on Network Level Analyses vs Project Level Analyses • Network Level Analyses – Consider the Pavement Distress Condition of All Our Roads – Used For Statewide Budgeting – Used for Performance Forecasting – Used for Reporting for Legislative Finance Committee on NM Performance Measures – Used for Transportation Asset Mgmt to meet FHWA Requirements – Composite Index Typically Used – Used for District Budgeting 9
Discussion on Network Level Analyses vs Project Level Analyses • Project Level Analyses – 2 Mile Sections Consider Prevalent Distress and Suggest Recommendation – Based on Decision Trees and Performance Curves and Cost:Benefit • Simply if Roadway has this types of distress or is this age, then X recommendation • Supplement w coring, field exploration, GPR, FWD – PavementME or MEPDG Input Data • Calibration of Pavement Distress Models • Materials Database • Traffic Database 10
Basics of Pavement Management Systems and Database (PMS db) • Inventory – What Is Important? – Pavement Condition Data – Roadway Segments, MP – Linear Referencing System (LRS) – Functional Classification – Pavement Section, Type – Shoulder Information – Number of Lanes – Construction History (1,900 Records) • Integration with MMS – Traffic Data and WIM Data – Materials Related Data – Cost Data 11
Pavement Condition Assessment • Types of Pavement Condition Data Collected – Distresses (FHWA LTPP Guide, 2014) – Structural Capacity • FWD? • RWD? • Traffic Speed Deflectomer? – Surface Characteristics • Friction? • Noise? • Techniques for Data Collection – Manual – Semi-Manual (NDT??) – Fully Automatic • NMDOT Since 2013 Moved to Fully Automatic 12
Pavement Condition Assessment • Applicable AASHTO Standards – R48: Standard Practice for Determining Rut Depth in Pavements – R36: Standard Practice for Evaluating Faulting of Concrete Pavements – R55: Standard Practice of Quantifying Cracks in Asphalt Pavement Surface – R43: Standard Practice for Quantifying Roughness of Pavements (IRI) 13
NMDOT PMS db Distresses Based on Long Term Pavement Performance LTPP FHWA Guidance • NMDOT Measures and Determines the Severity and Extent of Following Distresses – • Raveling and Weathering • Bleeding • Transverse Cracking • Alligator Cracks • Edge Cracks • Longitudinal Cracks • Patching • Block Cracking • IRI and Rutting …and concrete pavement distress too 14
Developing Pavement Condition Indices • What are Pavement Condition Indices? – Typically a numerical index between 0 to 100 which is used to indicate condition of pavement. • NMDOT use PCR (Pavement Condition Rating) Composite Index – – Subcategories • Composite Index • Individual Index – Composite Index • PCI, PCR, PSI – Individual Index • NMDOT uses Structural Index, Environmental, Safety Index, Roughness Index Evaluates Distress for Each Individual Index – Used for Decision Trees – 15
NMDOT PMS db History of Implementation 1990’s to 2006 (Fuzzy) • Districts Provided Assistance on Pavement Distress Data Collection – 2006 • NMSU and UNM Provided Manual Data Collection – PMS db Begins – 2012-2013 • Steering Committee Formed w District and General Office Representation and KEI – Engineering Hired to Help w Configuration Summer 2013 Executive Decision to move to Automated Distress Data Collection – Methods Requiring New Configuration of Agile PMS db – 2013-2017 • Moved to Automated, Mandli Data Collection – Reconfiguration – 2018 • Fugro – Reconfiguration Planned for Performance Curves based on Construction History – and Maintenance History data 16
The NMDOT Pavement Management System db Can… Assess Current and Future Pavement Conditions • Network Level Considerations and Analyze – Performance Curves and Modeling – Estimate Funding Needs to Achieve a Desired Condition • Level Budgeting – State of Good Repair – Identify Preservation, Rehabilitation and Reconstruction • Projects that Optimize Funding Project Level Analyses – Illustrate Consequences of Funding Levels on Condition • LFC, FHWA, TAMP Reporting – Performing Scenarios – Justify and Defend Funding Levels Compared to Performance – Reporting Methods • 17
PMS Data Collection Procedures • What type of distress are being collected • How is the data being collected • What control procedures are in place • Why are we collecting this information • How is this data being used 18
Data History Prior to automated collection NMDOT would collect IRI in house and contract a University to manual/visual survey and collect distress. Data definitions and some practices developed during manual survey were carried over to automated data collection 19
Data History New Mexico’s pavement distress definitions and collection methods were derived from FHWA’s Distress Identification and HPMS Manual along with data collection practices carried on from district distress field survey 20
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