Introduction and Applications

Transport and DevelopmentTransport sector is vital for economic & social developmentRoads constitute largest component of transportRoads require a balance of:Maintenance (or preservation)Development (or improvement)Road management requires:Consistent and rational policy objectivesSufficient and reliable fundingEffective procedures & management tools

The HDM-4 ModelAnalytical decision-making tool, based on life cycle costs, for: Engineering and economic assessment of road construction and maintenance investmentsTransport pricing and regulationPhysical and economic relationships derived from extensive research on:Road deterioration,The effects of maintenance activities, andRoad user costs (VOC, VOT, Crash Costs)Vehicle Emissions & Traffic Noise

HDM-4 Objectives:Economic basis for selecting investment alternatives

HDM-4 Objectives:Standard framework for investigating road investmentsMinimize Road Agency and Road User Costs

History of the HDM model

International Study of Highway Development and ManagementSponsors: World bankDept for international developmentAsian development bankOthersIn progress since 1993 comprising:Technical studies (1993~1997)Software development and testing (1996~1999)PIARC leading the implementation phase (1999 ~ )

HDM-4 Technology Set

HDM-4 Series

HDM-4 ConceptPredicts road network performance as a function of:Traffic volumes and loadingRoad pavement type and strengthMaintenance standardsEnvironment / ClimateQuantifies benefits to road users from:Savings in vehicle operating costs (VOC)Reduced road user travel timesDecrease in number of accidentsEnvironmental effects

Paved Road Deterioration ModelMoisture, Temperature AgingTraffic, LoadingPavement Materials, ThicknessCrackingRavelingPotholingRuttingRoughness

Road User Costs ModelRoad Geometry, ConditionDriver, Traffic FlowVehicle CharacteristicsSPEED Fuel & Lubricants Tire Maintenance Parts & Labor Crew Time Depreciation & Interest Passenger & cargo timeCOMPSUMPTION

Share of Transport Cost Components50 veh/day300 veh/day5000 veh/dayAgency CostsUser Costs

Optimum Transport CostsOptimumTotalRoad UserRoad WorksCostDesign Standards

How Credible are HDM-4 Outputs?Depends on Level of Calibration (controls bias)Depends on accuracy and reliability of input data (asset & fleet characteristics, conditions, usage)HDM-4 has proved suitable in a range of countriesAs with any model, need to carefully check output with good judgement

Approach to CalibrationInput dataMust have a correct interpretation of the input data requirementsHave a quality of input data appropriate for the desired reliability of resultsCalibrationAdjust model parameters to enhance the accuracy of its representation of local conditions3

Bias and Precision13

Data & CalibrationNeed to appreciate importance of data over calibrationIf input data are wrong why worry about calibration?

Calibration FocusRoad User EffectsPredict the correct magnitude of costs and relativity of components - dataPredict sensitivity to changing conditions - calibrationPavement Deterioration & Works EffectsReflect local pavement deterioration rates and sensitivity to factorsRepresent maintenance effects5

Important ConsiderationsCalibrate over full range of values likely to be encounteredHave sufficient data to detect the nature of bias and level of precisionHigh correlation (r 2) does not always mean high accuracy: can still have significant biasPrimary aim: minimize bias15

Calibration: Hierarchy of Effort

Calibration LevelsLevel 1: Basic ApplicationAddresses most critical parametersDesk StudyLevel 2: VerificationMeasures key parametersConducts limited field surveysLevel 3: AdaptationMajor field surveys to requantify relationshipsLong-term monitoring

Sensitivity Classes

Impact

Sensitivity Class

Impact Elasticity

High

S-I

> 0.50

Medium

S-II

0.20 0.50

Low

S-III

0.05 0.20

Negligible

S-IV

< 0.05

21

Sensitivity Class2/

Impact Elasticity

Parameter Important for Total VOC3/

Parameter Important for VOC Savings4/

S-I

> 0.50

kp - parts model exponent

New Vehicle Price

kp - parts model exponent

New Vehicle Price

CSPQI - parts model roughness term

C0SP - parts model constant term

S-II

0.20 - 0.50

Roughness

E0 - speed bias correction

Average Service Life Average Annual Utilisation

Vehicle Weight

E0 - speed bias correction

ARVMAX - max. rectified velocity

CLPC - labour model exponent

S-III

0.05 - 0.20

Aerodynamic Drag Coefficient

Beta - speed exponent

BW - speed width effect

Calibrated Engine Speed

CLPC - labour model exponent

C0SP - parts model constant term

CSPQI - parts model roughness term

Crew/Cargo/Passenger Cost

Desired Speed

Driving Power

Energy Efficiency Factors

Fuel Cost

Hourly Utilisation Ratio

Interest Rate

Projected Frontal Area

Beta - speed exponent

Vehicle Age in km

C0LH - labour model constant term

Labour Cost

Hourly Utilisation Ratio

BW - speed width effects

Number of tires per Vehicle

New tire Cost

Lubricants Cost

Crew/Cargo/Passenger Cost

Vehicle Weight

Number of Passengers

S-IV

22

Sensitivity

Impact

Parameter

Outcomes Most Impacted

Class

Elasticity

Pavement Performance

Resurfacing and Surface Distress

Economic Return on Maintenance

S-I

> 0.50

Structural Number 2/

(

(

(

Modified Structural Number2/

(

(

(

Traffic Volume

(

Deflection3/

(

(

(

Roughness

(

(

S-II

0.20 -

Annual Loading

(

(

(

0.50

Age

(

(

All cracking area

(

(

Wide cracking area

(

(

Roughness-environment factor

(

(

Cracking initiation factor

(

(

(

Cracking progression factor

(

S-III

0.05 -

Subgrade CBR (with SN)

(

0.20

Surface thickness (with SN)

(

(

Heavy axles volume

(

(

Potholing area

(

(

Rut depth mean

(

Rut depth standard deviation

(

Rut depth progression factor

(

Roughness general factor

(

(

S-IV

< 0.05

Deflection (with SNC)

(

Subgrade compaction

(

(

Rainfall (with Kge)

(

Ravelling area

(

Ravelling factor

(

Can We Believe HDM-4 Output?Yes, if sufficiently calibratedHDM-4 has proved suitable in a range of countriesAs with any model, need to carefully scrutinize output against judgementIf unexpected predictions occur, check: Data usedCalibration extentCheck judgment of the expert23

Applications of HDM-4 in Road ManagementPurpose: To optimise the overall performance of the network over time in accordance with POLICY OBJECTIVES and within budgetary constraintsTypical objectives:Minimise transport costsPreserve asset valueProvide and maintain accessibilityProvide safe and environmentally friendly transport

Road Management FunctionsPlanningSetting standards and policiesLong term estimates of expenditureProgrammingMedium term work programmesPreparationDetailed project design and work packagingOperationsImplementation of works in field

Role of HDM-4

Management Function

HDM-4 Application

Planning

Strategy Analysis

Programming

Programme Analysis

Preparation

Project Analysis

HDM-4 ApplicationsRoad sector policy studiesStrategic planning of road network development, improvement & maintenance Determination of funding requirementsPreparation of multi-year road work programmesEconomic appraisal of individual road projectsResearch studies

Standards & PoliciesRoad pricingroad use costs (to define fuel levies)congestion chargesweight-distance chargesVehicle regulationsaxle load limitsenergy consumption, vehicle emissions & noiseEngineering Standardssustainable road network sizepavement design and maintenance standards

Technical Standards400300200What is the optimal traffic threshold for paving?

Vehicle PoliciesHow much road damage is caused by trucks?

Strategy AnalysisObjectives:Determine budget allocations for road maintenance and improvementPrepare for work programmesDetermine long term network performanceAssess impact on road usersThe analysis of entire road networks to determine funding needs and/or to predict future performance under budget constraints

Strategic PlanningForecast scenarios of revenues & available budgetAssess current condition of assetsForecast traffic demands (from road network plan)Evaluate impact of strategies on performance and costs - using predictive modelOptimize strategies under alternative budget scenarios - maximize NPV for each scenarioDetermine multi-year program allocations & performance

Strategic Analysis ApproachRoad NetworkGFPLMHMatrixResource ConstraintsOptimal Strategy under Budgetary ConstraintsPreservation EvaluationOptimization ModuleRevenues, Sector budgetsDevelopment Candidates

Diagnostic of the Network

_961820684.xls

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Sheet: Sheet16

Area < 5%

5% < Area < 25%

Area> 25%

1433.0

1170.0

4762.0

< 3.5 IRI

3.5 < IRI < 5.0

> 5.0 IRI

2054.0

586.0

4725.0

National Highways Network Condition in 1998

Length

Length

(km)

(%)

(km)

(%)

Surface Type

Asphalt Concrete

2790.0

37.88187372708758

Roughness

< 3.5

2054.0

27.888662593346915

Surface Treatment

4575.0

62.11812627291242

(IRI)

3.5 - 5.0

586.0

7.9565512559402585

Total

5.0 - 7.0

1284.0

17.433808553971485

Traffic (ADT)

< 1000

1921.0

26.08282416836388

> 7.0

3441.0

46.72097759674134

1000 - 3000

1994.0

27.073998642226748

Total

3000 - 5000

946.0

12.844534962661236

Cracks Area

< 5

1433.0

19.456890699253222

5000 - 7000

1021.0

13.862864901561439

(%)

5 - 25

1170.0

15.885947046843176

> 7000

1483.0

20.135777325186694

> 25

4762.0

64.65716225390359

Total

Total

Cracks Area

Length

Roughness (IRI)

Length

Area < 5%

1433.0

< 3.5 IRI

2054.0

5% < Area < 25%

1170.0

3.5 < IRI < 5.0

586.0

Area> 25%

4762.0

> 5.0 IRI

4725.0

6.0

4.5

3.0

2.0

1.0

243.201

225.859

144.808

110.7

75.82

6.0

4.5

3.0

2.0

1.0

0.0

17.341999999999985

98.393

132.50099999999998

167.381

Net Present Value (Billion Rs)

Loss to Society

6.0

243.201

4.5

225.859

4.5

17.341999999999985

3.0

144.808

3.0

98.393

2.0

132.50099999999998

1.0

167.381

Consequences to SocietyWhat are the consequences of budget constraints? What is the recommended work program?

_961980491.xls

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Sheet: Sheet15

Sheet: Sheet16

Area < 5%

5% < Area < 25%

Area> 25%

1433.0

1170.0

4762.0

< 3.5 IRI

3.5 < IRI < 5.0

> 5.0 IRI

2054.0

586.0

4725.0


Length

Length

(km)

(%)

(km)

(%)

Surface Type

Asphalt Concrete

2790.0

37.88187372708758

Roughness

< 3.5

2054.0

27.888662593346915

Surface Treatment

4575.0

62.11812627291242

(IRI)

3.5 - 5.0

586.0

7.9565512559402585

Total

5.0 - 7.0

1284.0

17.433808553971485

Traffic (ADT)

< 1000

1921.0

26.08282416836388

> 7.0

3441.0

46.72097759674134

1000 - 3000

1994.0

27.073998642226748

Total

3000 - 5000

946.0

12.844534962661236

Cracks Area

< 5

1433.0

19.456890699253222

5000 - 7000

1021.0

13.862864901561439

(%)

5 - 25

1170.0

15.885947046843176

> 7000

1483.0

20.135777325186694

> 25

4762.0

64.65716225390359

Total

Total

Cracks Area

Length

Roughness (IRI)

Length

Area < 5%

1433.0

< 3.5 IRI

2054.0

5% < Area < 25%

1170.0

3.5 < IRI < 5.0

586.0

Area> 25%

4762.0

> 5.0 IRI

4725.0

6.0

4.5

3.0

2.0

1.0

243.201

225.859

144.808

110.7

75.82

6.0

4.5

3.0

2.0

1.0

0.0

17.341999999999985

98.393

132.50099999999998

167.381


Loss to Society

6.0

243.201

4.5

225.859

4.5

17.341999999999985

3.0

144.808

3.0

98.393

2.0

132.50099999999998

1.0

167.381

35.400000000000006

26.79

17.810000000000002

11.8

5.97

47.91

52.22000000000001

61.78999999999999

81.84

96.38999999999999

83.31

79.01000000000002

79.6

93.64

102.35999999999999

5.900000000000001

4.465

2.9683333333333337

1.9666666666666668

0.995

3.4221428571428567

3.730000000000001

4.413571428571428

5.845714285714286

6.884999999999999

42.2387395802754

37.021492878431424

32.267481962008674

34.23820456918895

35.128472690232414

1998.0

1998.0

1998.0

1998.0

1998.0

1999.0

1999.0

1999.0

1999.0

1999.0

2000.0

2000.0

2000.0

2000.0

2000.0

2001.0

2001.0

2001.0

2001.0

2001.0

2002.0

2002.0

2002.0

2002.0

2002.0

2003.0

2003.0

2003.0

2003.0

2003.0

2004.0

2004.0

2004.0

2004.0

2004.0

6.097610319076715

6.097610319076715

6.097610319076715

6.097610319076715

6.097610319076715

5.62

5.84

5.944670739986423

6.192735913102512

6.545349626612356

5.06

5.67

5.89

6.68

7.153238289205702

4.446381534283774

5.47

5.699823489477257

6.806422267481331

7.408906992532247

4.08

5.2

5.43

7.01

7.648472505091649

3.69

4.92

5.09

6.978085539714868

7.647970128988459

3.612084181941616

4.8

5.0

7.177162253903599

7.789260013577732

6.0

6.097610319076715

4.446381534283774

3.612084181941616

3.311133740665309

3.587997284453496

2.9359674134419556

3.0950848608282415

3.1715410726408693

3.1808553971486764

3.133754243041412

2.9851595383570944

2.6765241004752203

2.821466395112016

2.7943245078071963

2.785023761031908

2.880841819416158

2.7487712152070607

4.5

6.097610319076715

3.4389545145960625

3.7214528173794976

3.428499660556687

3.6694636795655122

3.359470468431772

3.182498302783435

3.077379497623897

3.2233129667345555

3.3653088934147997

2.992939579090292

2.9351391717583164

2.8849422946367955

3.03326544467074

2.9228649015614394

3.0

6.097610319076715

5.944670739986423

5.89

5.699823489477257

4.606245756958588

4.8519484046164285

4.528092328581127

4.793496266123557

3.80653088934148

3.803448744059742

3.445797691785472

3.3997827562797016

3.572735913102512

3.3794297352342157

3.2733604887983705

3.0974066530889344

3.178927359131025

3.2296673455532927

2.0

6.097610319076715

6.192735913102512

6.68

6.806422267481331

7.01

6.978085539714868

7.177162253903599

7.044589273591311

7.176890699253225

6.660515953835709

6.766571622539036

3.567847929395791

3.584276985743381

3.3736184657162256

3.218044806517312

3.3467209775967413

3.4408418194161574

3.3504955872369315

3.183679565512559

3.22847250509165

3.2654854039375425

1.0

6.097610319076715

6.545349626612356

7.153238289205702

7.408906992532247

7.648472505091649

7.647970128988459

7.789260013577732

7.775383570943652

7.9500067888662596

7.547264086897488

7.599090291921249

2.4653632043448748

2.591269517990496

2.686395112016293

2.5772301425661914

2.7124643584521384

2.7940665308893413

2.7757501697216567

2.9353021045485406

3.070549898167006

3.15816700610998

1.0

6.097610319076715

6.545349626612356

7.153238289205702

7.408906992532247

7.648472505091649

7.647970128988459

7.789260013577732

7.775383570943652

7.9500067888662596

7.547264086897488

7.599090291921249

2.4653632043448748

2.591269517990496

2.686395112016293

2.5772301425661914

2.7124643584521384

2.7940665308893413

2.7757501697216567

2.9353021045485406

3.070549898167006

3.15816700610998

0.0

6.097610319076715

6.726232179226069

7.356931432450781

7.790862186014935

8.070835030549897

8.348635437881873

8.536999321113374

8.746653088934147

8.987847929395791

9.220027155465038

9.427331975560081

3.0969450101832994

3.368608282416836

3.1568499660556686

3.359375424304141

3.273998642226748

3.300950441276307

2.9586965376782075

3.0268295994568906

3.0564426340801085

3.3350848608282417

Works for Scenario: 6 Billion Rs per Year

Works Years 1-6

Works per Year

km

Billion Rs

km

Billion Rs

25 mm DST

0.028333333333333335

30 mm TST

33.833333333333336

0.025

5 cm Overlay

0.3516666666666666

7.5 cm Overlay

1.2016666666666667

13 cm Overlay

62.666666666666664

0.555

15 cm Overlay

58.833333333333336

0.4683333333333333

30 cm Gran. Base / 15 cm AC

55.166666666666664

0.8866666666666667

30 cm Stab. Base / 8 cm AC

15 cm Gran. / 5 cm AC

329.6666666666667

0.965

Total

1053.1666666666667

5.901666666666667

Functional Overlays & Reseals

413.33333333333337

1.6066666666666667

Structural Overlays & Reconstructions

639.8333333333333

4.295

Total

1053.1666666666665

5.901666666666666

Asphalt Concrete Roads

Surface Treatment Roads

661.1666666666666

3.9466666666666668

Total

1053.1666666666665

5.901666666666667

N-25

693.0

2.449410484379767

115.5

0.4082350807299611

N-35

416.0

1.5108066321180722

69.33333333333333

0.25180110535301203

N-40

603.0

1.4165493573534702

100.5

0.2360915595589117

N-50

310.0

0.9481578843184608

51.666666666666664

0.1580263140530768

N-55

984.0

5.80584496198952

164.0

0.9676408269982533

N-5ACW

819.0

4.159495032763298

136.5

0.6932491721272163

N-5ECW

1670.0

15.390699828145747

278.3333333333333

2.5651166380242914

N-65

385.0

1.8619250322582217

64.16666666666667

0.3103208387097036

N-70

439.0

1.8671107866734435

73.16666666666667

0.3111851311122406

Total

1053.1666666666665

5.901666666666666

Consequences to the Network

_961829172.xls

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Sheet: Case 1

Sheet: Case 2

Sheet: Case 1 (2)

Sheet: Case 2 (2)

Islamic Republic of Pakistan

National Highways Network Evaluation

Scenario: 6 Billion Rs per Year

Road Condition (km)

Condition

Good

< 3.5 IRI

2054.0

3023.0

2809.0

4281.0

3627.0

5293.0

5293.0

Good

Fair

3.5 < IRI < 5.0

586.0

659.0

853.0

1110.0

1717.0

1417.0

1417.0

Fair

Poor / Very Poor

> 5.0 IRI

4725.0

3683.0

3703.0

1974.0

2021.0

655.0

655.0

Poor

7365.0

7365.0

7365.0

7365.0

7365.0

7365.0

7365.0

Avg. IRI

6.097610319076715

4.446381534283774

3.612084181941616

3.311133740665309

3.587997284453496

2.9359674134419556

3.0950848608282415

3.1715410726408693

3.1808553971486764

3.133754243041412

2.9851595383570944

2.6765241004752203

2.821466395112016

2.7943245078071963

2.785023761031908

2.880841819416158

2.7487712152070607

Road Condition (%)

Condition

1998.0

1999.0

2000.0

20001.0

2002.0

2003.0

2004.0

Good

< 3.5 IRI

0.27888662593346913

0.4104548540393754

0.38139850644942297

0.5812627291242363

0.4924643584521385

0.7186693822131704

0.7186693822131704

Fair

3.5 < IRI < 5.0

0.07956551255940258

0.08947725729803123

0.11581805838424983

0.15071283095723015

0.2331296673455533

0.19239646978954514

0.19239646978954514

Poor / Very Poor

> 5.0 IRI

0.6415478615071283

0.5000678886625933

0.5027834351663272

0.2680244399185336

0.2744059742023082

0.08893414799728445

0.08893414799728445

3.0881580957230144

1.0

1.0

1.0

1.0

1.0

1.0

1.0

Average Network Roughness (IRI)

6.097610319076715

5.62

5.06

4.446381534283774

4.08

3.69

3.69

Scenario: 0 Billion Rs per Year

Road Condition (km)

Condition

1998.0

1999.0

2000.0

20001.0

2002.0

2003.0

2004.0

Good

< 3.5 IRI

2054.0

1739.0

1525.0

741.0

0.0

0.0

0.0

Good

Fair

3.5 < IRI < 5.0

586.0

801.0

970.0

1451.0

2075.0

1585.0

1585.0

Fair

Poor / Very Poor

> 5.0 IRI

4725.0

4825.0

4870.0

5173.0

5290.0

5780.0

5780.0

Poor

7365.0

7365.0

7365.0

7365.0

7365.0

7365.0

7365.0

Avg. IRI

6.097610319076715

6.726232179226069

7.356931432450781

7.790862186014935

8.070835030549897

8.348635437881873

8.536999321113374

8.746653088934147

8.987847929395791

9.220027155465038

9.427331975560081

3.0969450101832994

3.368608282416836

3.1568499660556686

3.359375424304141

3.273998642226748

3.300950441276307

2.9586965376782075

3.0268295994568906

3.0564426340801085

3.3350848608282417

Road Condition (%)

Condition

1998.0

1999.0

2000.0

20001.0

2002.0

2003.0

2004.0

Good

< 3.5 IRI

0.27888662593346913

0.23611676849966057

0.20706042090970808

0.10061099796334012

0.0

0.0

0.0

Fair

3.5 < IRI < 5.0

0.07956551255940258

0.10875763747454176

0.131704005431093

0.19701289884589274

0.2817379497623897

0.2152070604209097

0.2152070604209097

Poor / Very Poor

> 5.0 IRI

0.6415478615071283

0.6551255940257977

0.6612355736591989

0.7023761031907672

0.7182620502376104

0.7847929395790902

0.7847929395790902

1.0

1.0

1.0

1.0

1.0

1.0

1.0


6.097610319076715

6.726232179226069

7.356931432450781

7.790862186014935

8.070835030549897

8.348635437881873

8.348635437881873

P_IRI1.XLS 26/5/98

1998.0

1999.0

1999.0

1999.0

1999.0

2000.0

2000.0

2000.0

2000.0

2001.0

2001.0

2001.0

2001.0

2002.0

2002.0

2002.0

2002.0

2003.0

2004.0

2054.0

586.0

4725.0

6.097610319076715

3023.0

659.0

3683.0

5.648472505091649

2809.0

853.0

3703.0

5.12

4281.0

1110.0

1974.0

4.446381534283774

3627.0

1717.0

2021.0

4.08

5293.0

1417.0

655.0

3.67

5166.0

1419.0

780.0

3.612084181941616

1998.0

1999.0

1999.0

1999.0

1999.0

2000.0

2000.0

2000.0

2000.0

2001.0

2001.0

2001.0

2001.0

2002.0

2002.0

2002.0

2002.0

2003.0

2004.0

2054.0

586.0

4725.0

6.097610319076715

1739.0

801.0

4825.0

6.726232179226069

1525.0

970.0

4870.0

7.356931432450781

741.0

1451.0

5173.0

7.790862186014935

0.0

2075.0

5290.0

8.070835030549897

0.0

1585.0

5780.0

8.348635437881873

0.0

1245.0

6120.0

8.536999321113374

1998.0

1999.0

1999.0

1999.0

1999.0

2000.0

2000.0

2000.0

2000.0

2001.0

2001.0

2001.0

2001.0

2002.0

2002.0

2002.0

2002.0

2003.0

2004.0

2054.0

586.0

4725.0

6.097610319076715

3023.0

659.0

3683.0

5.62

2809.0

853.0

3703.0

5.06

4281.0

1110.0

1974.0

4.446381534283774

3627.0

1717.0

2021.0

4.08

5293.0

1417.0

655.0

3.69

5166.0

1419.0

780.0

3.612084181941616

1998.0

1999.0

1999.0

1999.0

1999.0

2000.0

2000.0

2000.0

2000.0

2001.0

2001.0

2001.0

2001.0

2002.0

2002.0

2002.0

2002.0

2003.0

2004.0

2054.0

586.0

4725.0

6.097610319076715

1739.0

801.0

4825.0

6.726232179226069

1525.0

970.0

4870.0

7.356931432450781

741.0

1451.0

5173.0

7.790862186014935

0.0

2075.0

5290.0

8.070835030549897

0.0

1585.0

5780.0

8.348635437881873

0.0

1245.0

6120.0

8.536999321113374

Consequences to the Users

_961984274.xls

Sheet: Chart1

Sheet: Chart1 (2)

Sheet: Sheet1

Sheet: Chart2

Sheet: Chart2 (2)

Sheet: Sheet2

Sheet: Sheet3

Sheet: Chart3

Sheet: Sheet4

Sheet: Sheet5

Sheet: Sheet6

Sheet: Chart4

Sheet: Sheet7

Sheet: Sheet8

Sheet: Sheet9

Sheet: Sheet10

Sheet: Sheet11

Sheet: Sheet12

Sheet: Sheet13

Sheet: Sheet14

Sheet: Sheet15

Sheet: Sheet16

Area < 5%

5% < Area < 25%

Area> 25%

1433.0

1170.0

4762.0

< 3.5 IRI

3.5 < IRI < 5.0

> 5.0 IRI

2054.0

586.0

4725.0


Length

Length

(km)

(%)

(km)

(%)

Surface Type

Asphalt Concrete

2790.0

37.88187372708758

Roughness

< 3.5

2054.0

27.888662593346915

Surface Treatment

4575.0

62.11812627291242

(IRI)

3.5 - 5.0

586.0

7.9565512559402585

Total

5.0 - 7.0

1284.0

17.433808553971485

Traffic (ADT)

< 1000

1921.0

26.08282416836388

> 7.0

3441.0

46.72097759674134

1000 - 3000

1994.0

27.073998642226748

Total

3000 - 5000

946.0

12.844534962661236

Cracks Area

< 5

1433.0

19.456890699253222

5000 - 7000

1021.0

13.862864901561439

(%)

5 - 25

1170.0

15.885947046843176

> 7000

1483.0

20.135777325186694

> 25

4762.0

64.65716225390359

Total

Total

Cracks Area

Length

Roughness (IRI)

Length

Area < 5%

1433.0

< 3.5 IRI

2054.0

5% < Area < 25%

1170.0

3.5 < IRI < 5.0

586.0

Area> 25%

4762.0

> 5.0 IRI

4725.0

6.0

4.5

3.0

2.0

1.0

243.201

225.859

144.808

110.7

75.82

6.0

4.5

3.0

2.0

1.0

0.0

17.341999999999985

98.393

132.50099999999998

167.381


Loss to Society

6.0

243.201

4.5

225.859

4.5

17.341999999999985

3.0

144.808

3.0

98.393

2.0

132.50099999999998

1.0

167.381

35.400000000000006

26.79

17.810000000000002

11.8

5.97

47.91

52.22000000000001

61.78999999999999

81.84

96.38999999999999

83.31

79.01000000000002

79.6

93.64

102.35999999999999

5.900000000000001

4.465

2.9683333333333337

1.9666666666666668

0.995

3.4221428571428567

3.730000000000001

4.413571428571428

5.845714285714286

6.884999999999999

42.2387395802754

37.021492878431424

32.267481962008674

34.23820456918895

35.128472690232414

1998.0

1998.0

1998.0

1998.0

1998.0

1999.0

1999.0

1999.0

1999.0

1999.0

2000.0

2000.0

2000.0

2000.0

2000.0

2001.0

2001.0

2001.0

2001.0

2001.0

2002.0

2002.0

2002.0

2002.0

2002.0

2003.0

2003.0

2003.0

2003.0

2003.0

2004.0

2004.0

2004.0

2004.0

2004.0

6.097610319076715

6.097610319076715

6.097610319076715

6.097610319076715

6.097610319076715

5.62

5.84

5.944670739986423

6.192735913102512

6.545349626612356

5.06

5.67

5.89

6.68

7.153238289205702

4.446381534283774

5.47

5.699823489477257

6.806422267481331

7.408906992532247

4.08

5.2

5.43

7.01

7.648472505091649

3.69

4.92

5.09

6.978085539714868

7.647970128988459

3.612084181941616

4.8

5.0

7.177162253903599

7.789260013577732

6.0

6.097610319076715

4.446381534283774

3.612084181941616

3.311133740665309

3.587997284453496

2.9359674134419556

3.0950848608282415

3.1715410726408693

3.1808553971486764

3.133754243041412

2.9851595383570944

2.6765241004752203

2.821466395112016

2.7943245078071963

2.785023761031908

2.880841819416158

2.7487712152070607

4.5

6.097610319076715

3.4389545145960625

3.7214528173794976

3.428499660556687

3.6694636795655122

3.359470468431772

3.182498302783435

3.077379497623897

3.2233129667345555

3.3653088934147997

2.992939579090292

2.9351391717583164

2.8849422946367955

3.03326544467074

2.9228649015614394

3.0

6.097610319076715

5.944670739986423

5.89

5.699823489477257

4.606245756958588

4.8519484046164285

4.528092328581127

4.793496266123557

3.80653088934148

3.803448744059742

3.445797691785472

3.3997827562797016

3.572735913102512

3.3794297352342157

3.2733604887983705

3.0974066530889344

3.178927359131025

3.2296673455532927

2.0

6.097610319076715

6.192735913102512

6.68

6.806422267481331

7.01

6.978085539714868

7.177162253903599

7.044589273591311

7.176890699253225

6.660515953835709

6.766571622539036

3.567847929395791

3.584276985743381

3.3736184657162256

3.218044806517312

3.3467209775967413

3.4408418194161574

3.3504955872369315

3.183679565512559

3.22847250509165

3.2654854039375425

1.0

6.097610319076715

6.545349626612356

7.153238289205702

7.408906992532247

7.648472505091649

7.647970128988459

7.789260013577732

7.775383570943652

7.9500067888662596

7.547264086897488

7.599090291921249

2.4653632043448748

2.591269517990496

2.686395112016293

2.5772301425661914

2.7124643584521384

2.7940665308893413

2.7757501697216567

2.9353021045485406

3.070549898167006

3.15816700610998

1.0

6.097610319076715

6.545349626612356

7.153238289205702

7.408906992532247

7.648472505091649

7.647970128988459

7.789260013577732

7.775383570943652

7.9500067888662596

7.547264086897488

7.599090291921249

2.4653632043448748

2.591269517990496

2.686395112016293

2.5772301425661914

2.7124643584521384

2.7940665308893413

2.7757501697216567

2.9353021045485406

3.070549898167006

3.15816700610998

0.0

6.097610319076715

6.726232179226069

7.356931432450781

7.790862186014935

8.070835030549897

8.348635437881873

8.536999321113374

8.746653088934147

8.987847929395791

9.220027155465038

9.427331975560081

3.0969450101832994

3.368608282416836

3.1568499660556686

3.359375424304141

3.273998642226748

3.300950441276307

2.9586965376782075

3.0268295994568906

3.0564426340801085

3.3350848608282417

Works for Scenario: 6 Billion Rs per Year

Works Years 1-6

Works per Year

km

Billion Rs

km

Billion Rs

25 mm DST

0.028333333333333335

30 mm TST

33.833333333333336

0.025

5 cm Overlay

0.3516666666666666

7.5 cm Overlay

1.2016666666666667

13 cm Overlay

62.666666666666664

0.555

15 cm Overlay

58.833333333333336

0.4683333333333333

30 cm Gran. Base / 15 cm AC

55.166666666666664

0.8866666666666667

30 cm Stab. Base / 8 cm AC

15 cm Gran. / 5 cm AC

329.6666666666667

0.965

Total

1053.1666666666667

5.901666666666667

Functional Overlays & Reseals

413.33333333333337

1.6066666666666667

Structural Overlays & Reconstructions

639.8333333333333

4.295

Total

1053.1666666666665

5.901666666666666

Asphalt Concrete Roads

Surface Treatment Roads

661.1666666666666

3.9466666666666668

Total

1053.1666666666665

5.901666666666667

N-25

693.0

2.449410484379767

115.5

0.4082350807299611

N-35

416.0

1.5108066321180722

69.33333333333333

0.25180110535301203

N-40

603.0

1.4165493573534702

100.5

0.2360915595589117

N-50

310.0

0.9481578843184608

51.666666666666664

0.1580263140530768

N-55

984.0

5.80584496198952

164.0

0.9676408269982533

N-5ACW

819.0

4.159495032763298

136.5

0.6932491721272163

N-5ECW

1670.0

15.390699828145747

278.3333333333333

2.5651166380242914

N-65

385.0

1.8619250322582217

64.16666666666667

0.3103208387097036

N-70

439.0

1.8671107866734435

73.16666666666667

0.3111851311122406

Total

1053.1666666666665

5.901666666666666

6 Billion Rs per Year Case

140.065

138.00599999999997

158.82399999999996

161.285

Without Project Case

140.065

154.501

168.595

181.476

194.74100000000007

208.86699999999993

896.2949999999998

1048.2450000000001

151.95000000000027

36.0

1999.0

1999.0

2000.0

2000.0

2001.0

2001.0

2002.0

2002.0

2003.0

2003.0

2004.0

2004.0

140.065

140.065

138.00599999999997

154.501

149.12

168.595

148.995

181.476

158.82399999999996

194.74100000000007

161.285

208.86699999999993

Impact of Budget Levels

_1135753183.xls

Chart1

1433

1170

4762

&A

Page &P

Length

Cracks Area in 1998

Chart1 (2)

2054

586

4725

&A

Page &P

Length

Roughness in 1998

Sheet1


LengthLength

(km)(%)(km)(%)

Surface TypeAsphalt Concrete279038Roughness< 3.5205428

Surface Treatment457562(IRI)3.5 - 5.05868

Total73651005.0 - 7.0128417

Traffic (ADT)< 1000192126> 7.0344147

1000 - 3000199427Total7365100

3000 - 500094613Cracks Area< 5143319

5000 - 7000102114(%)5 - 25117016

> 7000148320> 25476265

Total7365100Total7365100

Cracks AreaLengthRoughness (IRI)Length

Area < 5%1433< 3.5 IRI2054

5% < Area < 25%11703.5 < IRI < 5.0586

Area> 25%4762> 5.0 IRI4725

&A

Page &P

Chart2

243.201

225.859

144.808

110.7

75.82

&A

Page &P


Periodic Expenditures (Billion Rs/year)

Society Net Benefits Present Value (Billion Rs)

Chart2 (2)

0

17.342

98.393

132.501

167.381

&A

Page &P

Loss to Society

Periodic Expenditures (Billion Rs/year)

Society Loss Present Value (Billion Rs)

Sheet2

Net Present Value (Billion Rs)Loss to Society

6243.20160

4.5225.8594.517.342

3144.808398.393

2110.72132.501

175.821167.381

&A

Page &P

Sheet3

64.5321

1128.985.973.971.98

200000

311.998.995.943.921.99

400000

511.418.825.93.912

600000

74.858.345.133.171.91

80.060.130.850.790.06

910.97.897.497.346.52

100.560.350.560.560.35

111.416.4418.3847.7775.71

122.995.112.5720.8

133.012.695.092.630.43

144.940.793.043.53.3

157.341.590.90.710.07

160.347.725.641.510.95

172.952.953.813.262.29

182.262.63.794.130.74

191.180.741.941.61.13

205.124.882.62.872.13

35.426.817.811.86.0

47.952.261.881.896.4

83.379.079.693.6102.4

5.94.53.02.01.0

3.43.74.45.86.9

$42.24$37.02$32.27$34.24$35.13

&A

Page &P

Chart3

6.09761031916.09761031916.09761031916.09761031916.0976103191

5.625.845.944670746.19273591316.5453496266

5.065.675.896.687.1532382892

4.44638153435.475.69982348956.80642226757.4089069925

4.085.25.437.017.6484725051

3.694.925.096.97808553977.647970129

3.61208418194.857.17716225397.7892600136

&A

Page &P

6.0

3.0

4.5

2.0

1.0

BudgetScenarios(Rs B per year)

6.0

4.5

3.0

2.0

1.0

Year


Sheet4

199819992000200120022003200420052006200720082009201020112012201320142015201620172018

6.06.09761031915.625.064.44638153434.083.693.61208418193.31113374073.58799728452.93596741343.09508486083.17154107263.18085539713.1337542432.98515953842.67652410052.82146639512.79432450782.7850237612.88084181942.7487712152

4.56.09761031915.845.675.475.24.924.83.43895451463.72145281743.42849966063.66946367963.35947046843.18249830283.07737949763.22331296673.36530889342.99293957912.93513917182.88494229463.03326544472.9228649016

3.06.09761031915.944670745.895.69982348955.435.0954.6062457574.85194840464.52809232864.79349626613.80653088933.80344874413.44579769183.39978275633.57273591313.37942973523.27336048883.09740665313.17892735913.2296673456

2.06.09761031916.19273591316.686.80642226757.016.97808553977.17716225397.04458927367.17689069936.66051595386.76657162253.56784792943.58427698573.37361846573.21804480653.34672097763.44084181943.35049558723.18367956553.22847250513.2654854039

1.06.09761031916.54534962667.15323828927.40890699257.64847250517.6479701297.78926001367.77538357097.95000678897.54726408697.59909029192.46536320432.5912695182.6863951122.57723014262.71246435852.79406653092.77575016972.93530210453.07054989823.1581670061

1.06.09761031916.54534962667.15323828927.40890699257.64847250517.6479701297.78926001367.77538357097.95000678897.54726408697.59909029192.46536320432.5912695182.6863951122.57723014262.71246435852.79406653092.77575016972.93530210453.07054989823.1581670061

0.06.09761031916.72623217927.35693143257.7908621868.07083503058.34863543798.53699932118.74665308898.98784792949.22002715559.42733197563.09694501023.36860828243.15684996613.35937542433.27399864223.30095044132.95869653773.02682959953.05644263413.3350848608

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Sheet7

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Sheet8

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Sheet9

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Sheet10

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Sheet11

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Impact of Budget AllocationsFeederRoads$30m/yrSecondaryRoads$35m/yrPrimaryRoads$20m/yr

Programme AnalysisObjective: prioritise candidate road projects in each year within annual budget constraintAnnual budgets obtained from strategic maintenance planPreparation of single or multi-year road work and expenditure programmes under specified budget constraints.

Work Programme Output

Project Economic AnalysisProject typesNew construction, upgradingReconstruction, resealingWidening, lane additionNon-motorised transport lanesEconomic indicatorsNet present value (NPV)Economic rate of return (ERR)Benefit cost ratio (BCR), NPV/CFirst year rate of return (FYRR)

Economic Decision CriteriaNPV IRR(3)NPV/CFYRRProject economic validityV.GoodV.GoodV.GoodPoorMutually exclusive projectsV.GoodPoorGoodPoorProject timingFairPoorPoorGoodProject screening (1)PoorV.GoodGoodPoorUnder budget constraint (2)FairPoorV.GoodPoor

Notes:(1)Check for robustness to changes in key variables (sensitivity analysis)(2)With incremental analysis(3)IRR may be indeterminate with NONE or MANY solutions.

Project Level OutputsSensitivity analysis resultsScenario analysisRoad condition indicatorsRoad user cost detailsEnergy & emissions

HDM-4 LimitationsThe model does not:Perform a network traffic assignmentInternally cost environmental impacts such as air or noise pollutionAddress urban conditions (start/stop)Evaluate all benefits from very low volume roadsSoftware limitations:Not designed as a road management database

Conclusions Why HDM-4?Transparency of analysisEconomic analysis capable of:Short, medium & long term analysesWhat-if analysisInternationally accepted analysis frameworkAvailability of technical expertiseLocal calibration

Web sites:http://hdm4.piarc.orghttp://www.bham.ac.uk/isohdmhttp://lpcb.org

The first move towards producing a road project appraisal model was made in 1968 by the World Bank. The first model was produced by MIT following a literature survey and was based mainly on a framework proposed by de Weille. The resulting Highway Cost Model (HCM) highlighted areas where more research was needed to provide a model that was more appropriate to developing country environments with additional specific relationships.Following this, TRRL, in collaboration with the World Bank, undertook a major field study in Kenya to investigate the deterioration of paved and unpaved roads as well as the factors affecting vehicle-operating costs in a developing country. The results of this study were used by TRRL to produce the first prototype version of the Road Transport Investment Model (RTIM) for developing countries. In 1976, the World Bank funded further developments of the HCM at MIT that produced the first version of the Highway Design and Maintenance Standards model (HDMII).Further work was undertaken in a number of countries to extend the geographic scope of the RTIM and HDM models, including; the Caribbean Study by TRRL which investigated the effects of road geometry on vehicle operating costs, the India Study by the Central Road Research Institute which studied particular operational problems of Indian roads in terms of narrow pavements and large proportions of non-motorised transport, and the Brazil Study funded by UNDP, which extended the validity of all of the model relationships.The Highway Design and Maintenance Standards Model (HDM-III), developed by the World Bank, has been used for over two decades to combine technical and economic appraisals of road investment projects, and to analyse strategies and standards. An international study has been carried out to extend the scope of the HDM-III model, and to provide a harmonised systems approach to road management, with adaptable and user-friendly software tools. This has resulted in the development of the Highway Development and Management Tool (HDM-4). The ISOHDM project was sponsored by the Asian Development Bank (ADB), the UK Department for International Development (DFID), the World Bank, and the Swedish National Road Administration (SNRA).

The HDM-4 analytical framework is based on the concept of pavement life cycle analysis. This is applied to predict the following over the life cycle of a road pavement, which is typically 15 to 40 years:Road deteriorationRoad work effectsRoad user effectsSocio - Economic and Environmental effectsOnce constructed, road pavements deteriorate as a consequence of several factors, most notably:Traffic loadingEnvironmental weatheringEffect of inadequate drainage system

3135152122231. Another way of defining the purpose would be to maintain and improve the existing road network to enable its continued use by traffic in an efficient, safe and environmentally appropriate manner. 1. These are fairly self explanatory but the trainers should develop typical brief examples from their own countries.

Planning - setting standards, broad network, not spatial (e.g. we are concerned with the issue $x spent on the national network over the next y years would result in z% of the network having a roughness less than...Programming - works programmes at network level (1,5 year programmes etc)Preparation - detailed designs and work packagesOperations - managing the work and scheduling work, monitoring costs etc

1. Will be discussing the details of the different applications of HDM-4 in later sessions, but this provides an overview. HDM-4 is a decision support system and helps us with the above functions.

2. Note that HDM-4 only has its own database developed specifically for the various analyses which it carries out. It is not a road management system, or pavement management system, in its own right although data can be imported from such systems for use in HDM-4. 2The slide summarises the main uses of economic decision criteria. It can be seen that each criteria has its strengths and weaknesses..The NPVs strength is its ability to choose between mutually exclusive projects. It is however poor in dealing with uncertainty as is the case for initial project screening, when the future planning discount rate or other assumptions are relatively uncertain. Cumbersome continuous recalculations are needed to deal with project timing or budget constraints.The IRRs strength is its ability rank projects when there is uncertainty about assumptions. Its weakness is it ability to choose between mutually exclusive projects.The NPV/Cs strength is its ability to deal with budget constraints. It has more good points than the other criteria but it is a little more complicated to use especially with mutually exclusive projects when incremental analysis is required.The FYRR main purpose is to provide guidance on project timing- but even here it is far from being completely reliable. It is weak in all other aspects.

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Introduction and Applications