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

2. Road Deterioration and Works Effects Modelling

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

4. 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

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

6. 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

7. Start Point Critical For Predictions7

8. Bituminous Pavement Classes8

9. 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

10. 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

11. 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

12. 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

13. Interactions Between Distresses1
Water
ingress
Further
cracking
Patches
Shear
Uneven
surface
Spalling
Faster
deformation
ROUGHNESS
Potholes
Time
Surface
Lower strength
Area of
Cracking
Rut
depth 13

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

15. Cracking Initiation –Calibration15

16. Cracking Progression Calibration16

17. 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

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

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

20. 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

21. 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

22. 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

23. Maintenance Effects
Depending on distress maintenance has different effects 23

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

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

26. Road User Effect Modelling26

27. Components of RUE 27

28. Factors Influencing RUE28

29. Fuel Consumption
Predicts fuel use as function of power usage 29

30. HDM-4 Speed-Flow Model 30

31. Recommended Model Parameters31

32. Validity of Speed-Flow Model32

33. 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

34. Congestion Modelling 34

35. 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

36. Flow on Additional Fuel36

37. Effect of Congestion on Tyre Consumption37

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

39. Parts vs Roughness Effects39

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

41. Roughness on Depreciation41

42. 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

43. 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

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

45. 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

46. 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

47. 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

48. Calibration Very Important48

49. The End