The International Study of Highway Development and Management Tools The World Bank Dr. Christopher R Bennett Senior Transport Specialist

“The farther back you look, the farther forward you are likely to see” Winston Churchill

Presentation Outline l ISOHDM: Objectives and Outputs l Road Deterioration and Works Effects Modelling l Calibration Issues l Experiences From Some Developed Countries l The Future

ISOHDM: Objectives and Outputs

OtherContributors SNRA SweRoad VTI TechnicalAdvisors DFID The University of Birmingham ADB N D Lea Int. IKRAM FICEM ICH (Chile) Catholic Univ. Sponsors Department for International Development (DFID) Asian Development Bank (ADB) Swedish National Road Administration (SNRA) The World Bank (IBRD) Steering Committee (The World Bank) Secretariat The University of Birmingham

Objectives l Standardise economic and technical analysis of road expenditures l Rationalise planning, programming, budgeting, appraisal & policy formulation l Improve technical capabilities of HDM-III l Use modern IT environment and techniques

What is HDM? l International Study of Highway Development and Management Tools (ISOHDM) had 3 outputs: –Techniques for optimising investments in roads –Mathematical models for predicting road deterioration, works effects, and their impact on road users –Software package for applying techniques and models

Where is HDM-4 Software Registered?

Who Registered HDM-4?

ISOHDM Technical Reports

Using the ISOHDM Outputs l Many countries have adopted the HDM-4 techniques and some/all the models but not the software: –Australia –Greece –India –New Zealand –Thailand l Companies supply software which compete with HDM-4 (eg dTIMS, ARRB TR)

Road Deterioration and Works Effects Modelling

Road Deterioration Modelling l Pavement Management Systems (PMS) must have some form of modelling capability l Objective is to predict the future condition and the effects of maintenance

What We are Trying to Predict ASSET CONDITION EXCELLENT POOR TIME Minimum Acceptable Standard (TRIGGER) Decay in Condition (DETERIORATION) Treatment Applied Condition Improvement (RESET)

Road Deterioration Depends On l Original design l Material types l Construction quality l Traffic volume and axle loading l Road geometry l Pavement age l Environmental conditions l Maintenance policy

Types of Models Deterministic l Predict that there is a set outcome of an event l Used for network or project analyses l Give detailed work programme for a section Probabilistic l Predict that there is a probability of an outcome l Used for network analyses l Cannot give detailed work programme for a section

Deterministic Models l Various techniques for developing models: –Empirical models –Mechanistic-Empirical (structured empirical) models –Mechanistic models –Bayesian models

Deterministic Models... l Mechanistic based models –offer greater flexibility than regression models –More easily transferred to different pavements or conditions –very data intensive l Structured empirical approach –Used in HDM –Knowledge of how pavements perform used to set framework for statistical analysis –Much less data intensive

Probabilistic Models l Usually based on Markov-Chain

Types of Deterministic Models l Absolute –Predicts the future condition CONDITION = f(a0, a1, a2) –Limited to conditions model developed for –Problems with calibration l Incremental –Predicts the change in condition from the current condition:  CONDITION = f(a0, a1, a2) –Can use any start point so much more flexible

BituminousConcreteBlock*Unsealed Cracking Rutting Ravelling Potholing Roughness Edge break Surface texture Skid resistance Cracking Joint spalling Faulting Failures Serviceability rating Roughness Rutting Surface texture Roughness *not in current release Gravel loss Roughness Pavement Defects Modelled in HDM-4 Plus deterioration of drains

Models Designed for Range of Conditions l Moisture –Arid –Semi-arid –Sub-humid –Humid –Per-humid l Temperature – –Tropical – –Sub-tropical hot – –Sub-tropical cool – –Temperate cool – –Temperate freeze

Deterioration Models - Bituminous POTHOLING CRACKING Structural Thermal Reflection ROUGHNESS Cracking Rutting Potholing Structural Patching Environment RAVELLING RUTTING Structural Deformation Plastic Deformation Surface Wear Initial Densification

Deterioration Models - Concrete Cracking% of slabs crackedJP Number per kmJR FaultingmmJP,JR Spalling% of transverseJP,JR joints FailuresNumber per kmCR ServiceabilityDimensionlessJR,CR Roughnessm/km IRIAll

Interactions Between Distresses t 1 t 1 Water ingress Further cracking Patches Shear Uneven surface Spalling Faster deformation ROUGHNESS Potholes Patches Time Uneven Surface Lower strength Area of Cracking Rut depth

Initiation and Progression Periods INITIATION PROGRESSION Pavement Age (years) Cracked Area (%) l Cracking, ravelling and potholing have initiation and progression periods

Cracking Initiation – Local Calibration

Cracking Progression – Local Calibration

Roughness l Roughness = F(age, strength, potholes, cracking, ravelling, rutting) Roughness (IRI) Treatment Do Nothing Year

Rut Depth Components

Rutting l Rutting = F(age, traffic, strength, compaction) Pavement Age (Years) Rutting (mm) Weak Pavement Strong Pavement

Example of Predictions for 3 Different Pavements Independent Variable Index Current Condition Different Slopes A C B

Progression of Distresses l Can group deterioration into: –Surface –Structural l Surface deterioration can be halted at almost any point by maintenance l Structural deterioration rates can be reduced by maintenance, but never halted

Deterioration Management EXCELLENT POOR TIME ORIGINAL DECAY OPTIMAL CONDITION BAND OPTIMAL RENEWAL STRATEGY Maintenance Treatments

Steps for PMS Analysis l Establish key data on the pavements l Predict pavement deterioration over time and under traffic l Predict maintenance effects l Evaluate results

Road Work Classification Preservation –Routine l Patching, Edge repair l Drainage, Crack sealing –Periodic l Preventive treatments l Rehabilitation l Pavement reconstruction –Special l Emergencies l Winter maintenance Development –Improvements l Widening l Realignment l Off-carriageway works –Construction l Upgrading l New sections

Maintenance Interventions l Scheduled –Fixed intervals of time between interventions –Interventions at fixed points of time l Responsive –Pavement condition –Pavement strength –Surface age –Traffic volumes/loadings –Accident rates

Road Maintenance & Improvement l Affects long term pavement performance l Funding requirements depend on specified maintenance standards & unit costs Roughness Rehabilitation Time (years) or Traffic Loading Maintenance Standard Pavement Performance Curve Good Poor

Maintenance Effects l Depending on distress maintenance has different effects

Maintenance May Affect l Pavement strength l Pavement condition l Pavement history l Maintenance cost REMEMBER … the type of treatment dictates what it will influence

Calibration Issues

Reliability of Results Depends On: l How well the available data represent the real conditions to HDM l How well the model’s predictions fit the real behaviour and respond to prevailing conditions

Time Spend on Different Phases of Analysis Establishing Reliable Input Data 40% Model Calibration 10% Treatments, Triggers and Resets 20% Running dTIMS 10% Verification of Output 20%

Estimating Calibration Coefficients Un-calibrated Calibrated

Data vs Calibration l Need to appreciate importance of data over calibration l If input data are wrong why worry about calibration?

Application of Model l Input Data –Must have a correct interpretation of the input data requirements –Have a quality of input data appropriate for the desired reliability of results l Calibration –Adjust model parameters to enhance the accuracy of its representation of local conditions

Confidence in Predictions Over Time Time Condition Existing Condition Confidence Interval Trigger Interval Criteria for Intervention

Implications of Data on Predictions Trigger Interval Time Condition Existing Condition Confidence Interval Criteria for Intervention

Calibration Adjustments

Hierarchy of Effort

Bias and Precision

For Further Information l A guide to calibration and adaptation l Reports on various HDM calibrations from:

Experiences From Some Developed Countries l New Zealand l Greece

New Zealand

New Zealand is l Geologically VERY young –Many difficult soils l Geologically VERY variable –Many different subgrade conditions –Many different construction materials l Environmentally variable –Many different climatic zones

Typical New Zealand Road

New Zealand l Implemented HDM pavement deterioration models into dTIMS software platform l dTIMS used by all local authorities l Bituminous and unsealed roads modelled l Use both economic non-economic approaches

Stages of a Project dTIMS Strategic Planning Maintenance Budget Maintenance Programming Treatments Locations Project Preparation Tender Documents Implementation Funding Allocations

Maximise Saving in VOC Time Analysis Period Strategy Do-nothing VOC Benefit

Area Under Curve (AUC) Composite Index Time Analysis Period Strategy Do-nothing Benefit

Treatment Generic Types Adopted Resurfacing Large Chip Resurfacing Small Chip Resurfacing Double Chip Resurfacing Special Resurfacing Strengthening Reconstruction AC Reconstruction ST Thick Asphalt Overlay Thick Granular Overlay Smoothing Thin Asphalt Overlay Thin Granular Overlay Rip and Replace ST Rip and Remake AC Mill and Replace AC Unsealed Upgrade to Surfaced Regravel Grading and Routine

Maintenance l Maintenance treatments triggered –As a function of individual distresses –Using composite index comprised of cracking, flushing, rut depth and age l Initially were successful at about 60% of what engineer’s estimated, improved to over 90% after 2 years of refinement

Trigger Limits (Performance Std.) Independent Variable Do-Nothing Index Resurface Recon. Smoothing

Calibration l Success of project has led to interest in calibration l 60+ sites established in 2001 on state highways l 80+ more starting 2003 on local authority roads

Greece

Adaptation to Greece Default Models Calibrated to Greece

Greek Calibration l Improved modelling of pavement strength through new set of comprehensive models –Method for estimating remaining life and structural capacity –Simple method for establishing strength of a pavement l Cracking models –Calibrated to slower progression and different initiation –Modified model to handle extent and severity –Allowed cracking and ravelling to co-exist

Greek Calibration … l Roughness –Modified model to have all components sensitive to climate and traffic l LTPP –When tested against LTPP data models gave good results

The Future

Progress… l Since 2000 focus of ISOHDM has been on the software l Version 2 to be released in early 2004 l HDM-4 is being put on a commercial basis by PIARC –5 to 10 year concession for management of software –Responsible for enhancing documentation and identifying future technical enhancements

What Needs to Be Done? l Several countries collecting LTPP data –Potential for developing enhanced or new deterioration models l Regional calibration –As HDM or its models are applied more widely can build on the experiences to improve calibration factors l Enhancements to vehicle operating cost models

Summary

ISOHDM Study l Has provided a good foundation for rational investments in roads l Integrated framework between pavement deterioration, maintenance and road user effects l Models have been successfully applied –In developed and developing countries –From dry to humid environments –From tropical to freeze-thaw climates l The 7 technical reference manuals give detailed background information

The End