HDM-4: Pavement Deterioration Modeling and Road User Effects Christopher R. Bennett EASTE

Road Deterioration and Works Effects Modelling

Road Deterioration Modelling Objective is to predict future condition of roads over time and under traffic the effects of maintenance 3

What We are Trying to Predict Decay in Condition (DETERIORATION) EXCELLENT Condition Improvement (RESET) ASSET CONDITION Minimum Acceptable Standard (TRIGGER) Treatment Applied POOR TIME 4

Road Deterioration Depends On Original design Material types Construction quality Traffic volume and axle loading Road geometry Pavement age Environmental conditions Maintenance policy 5

HDM Models HDM uses ‘Deterministic Models’ Predicts a single future outcome based on current situation Developed using ‘structured empirical approach’ Knowledge of how pavements perform used to set framework for statistical analysis Incremental Change in condition based on current condition:  CONDITION = f(a0, a1, a2) Can use any start point so flexible 6

Start Point Critical For Predictions 7

Bituminous Pavement Classes 8

Plus deterioration of drains Distresses Modeled Bituminous Concrete Block* Unsealed Cracking Rutting Ravelling Potholing Roughness Edge break Surface texture Skid resistance Joint spalling Faulting Failures Serviceability rating *not in software Gravel loss Plus deterioration of drains 9

Models Designed for Range of Conditions Moisture Arid Semi-arid Sub-humid Humid Per-humid Temperature Tropical Sub-Tropical hot Sub-Tropical Cool Temperate Cool Temperate Frees 10

Deterioration Models - Bituminous CRACKING Structural Thermal Reflection ROUGHNESS Cracking Rutting Potholing Patching Environment RAVELLING RUTTING Structural Deformation Plastic Deformation Surface Wear Initial Densification POTHOLING 11

Det. Models - Concrete Cracking % of slabs cracked JP Number per km JR Faulting mm JP,JR Spalling % of transverse JP,JR joints Failures Number per km CR Serviceability Dimensionless JR,CR Roughness m/km IRI All 12

Interactions Between Distresses 1 Water ingress Further cracking Patches Shear Uneven surface Spalling Faster deformation ROUGHNESS Potholes Time Surface Lower strength Area of Cracking Rut depth 13

Initiation and Progression Cracking, raveling and potholing have initiation and progression periods Pavement Age (years) Cracked Area (%) INITIATION PROGRESSION 14

Cracking Initiation –Calibration 15

Cracking Progression Calibration 16

Roughness Roughness = F(age, strength, potholes, cracking, raveling, rutting) 2 4 6 8 10 12 14 1 11 16 Roughness (IRI) Treatment Do Nothing Year 17

Rutting Rutting = F(age, traffic, strength, compaction) Rutting (mm) Pavement Age (Years) Rutting (mm) Weak Pavement Strong Pavement 18

Example of Predictions Independent Variable Index Current Condition C B Different Slopes A 19

Road Works Classification Preservation Routine Patching, Edge repair Drainage, Crack sealing Periodic Preventive treatments Rehabilitation Pavement reconstruction Special Emergencies Winter maintenance Development Improvements Widening Realignment Off-carriageway works Construction Upgrading New sections 20

Maintenance Interventions Scheduled Fixed intervals of time between interventions Interventions at fixed points of time Responsive Pavement condition Pavement strength Surface age Traffic volumes/loadings Accident rates 21

Maintenance & Improvement Affects long term pavement performance Funding requirements depend on specified maintenance standards & unit costs Poor Maintenance Standard Roughness The figure illustrates the predicted trend in pavement performance represented by the riding quality that is often measured in terms of the international roughness index (IRI). When a maintenance standard is defined, it imposes a limit to the level of deterioration that a pavement is permitted to attain. Consequently, in addition to the capital costs of road construction, the total costs that are incurred by road agencies will include the periodic maintenance, or rehabilitation works applied during the life of a pavement. These in turn depend on the standards of maintenance and improvement specified by HDM-4 users. Pavement Performance Curve Rehabilitation Good Time (years) or Traffic Loading 22

Maintenance Effects Depending on distress maintenance has different effects 23

Maintenance May Affect Pavement strength Pavement condition Pavement history Maintenance cost REMEMBER … the type of treatment dictates what it will influence 24

Deterioration Management EXCELLENT POOR TIME ORIGINAL DECAY OPTIMAL CONDITION BAND OPTIMAL RENEWAL STRATEGY Maintenance Treatments 25

Road User Effect Modelling 26

Components of RUE 27

Factors Influencing RUE 28

Fuel Consumption Predicts fuel use as function of power usage 29

HDM-4 Speed-Flow Model 30

Recommended Model Parameters 31

Validity of Speed-Flow Model 32

Congestion - Fuel Model 3-Zone model predicts as flows increase so do traffic interactions As interactions increase so do accelerations and decelerations Adopted concept of ‘acceleration noise’ -- the standard deviation of acceleration 33

Congestion Modelling 34

Traffic Noise Modelled using sigmoidal function Integrated with Three-zone Model The maximum traffic noise and ratio Q0/Qult governs predictions Easy to calibrate 35

Flow on Additional Fuel 36

Effect of Congestion on Tyre Consumption 37

Parts and Labour Costs Usually largest single component of VOC Few studies were found to have calibrated model 38

Parts vs Roughness Effects 39

Capital Costs Comprised of depreciation and interest costs HDM-4 uses ‘Optimal Life’ method or constant life method 40

Roughness on Depreciation 41

Work Zones Cause traffic interruptions due to vehicles having to stop or reduced capacities Uses speed-cycle results for calculating costs Have software application for performing analyses Gives delays and queue sizes based on length of road closure 42

Safety HDM-4 does not predict accident rates User defines a series of “look-up tables” of accident rates The rates are broad, macro descriptions relating accidents to a particular set of road attributes Fatal Injury Damage only 43

Accident Groups Road type, class, use Traffic level Geometry, pavement type, ride quality, surface texture, presence of shoulders Non-motorised traffic Intersection type 44

Emissions Model Developed by VTI in Sweden Conducted statistical analysis of emissions as function of fuel use Developed simple linear model Model will be changed in future 45

Energy Balance Analysis Compares total life-cycle energy consumption of different transport policies Three energy use categories: Motorised vehicles Non-motorised vehicles Road construction and maintenance 46

Energy Analysis Output Total energy consumption Total consumption of renewable and non-renewable energy Total national and global energy use Specific energy consumption (per km) 47

Calibration Very Important 48

The End