Cesar Queiroz, Ph.D. Consultant, former World Bank Highways Adviser

Maputo, Mozambique, 4-8 November 2013

Road Network Evaluation Tools:Overview, Main Concepts, Applications

Administração Nacional de Estradas (ANE)

RONET Overview, Main Concepts, Background and Applications

• Infrastructure and economic development• Optimization defined• A common concern: how to optimize

maintenance and rehabilitation• What is required for an agency to use

RONET? • RONET structure• RONET applications• Next steps

Infrastructure• “The built environment in which we

live” (Ausubel and Herman)• The physical framework upon

which the economy operates and our standard of living depends (ASCE)

Infrastructure comprises• Public utilities: power,

telecommunications, piped water supply, sanitation and sewerage, solid waste collection and disposal, piped gas

• Public works: roads, dams, canals, railways, ports, waterways, airports, buildings

Developing and Developed Countries• Developing countries include low- and middle-

income economies• Developed (advanced, industrial, rich) countries

denote high-income economies• The World Bank’s main criterion for classifying

economies is gross national income (GNI) per capita, previously referred to as gross national product (GNP)

• http://data.worldbank.org/indicator/NY.GNP.PCAP.CD

Classification of EconomiesEconomies GNI per capita

Low-income $1,035 or lessMiddle-Income $1,036 to $12,615

Lower $1,036 to $4,085Upper $4,086 to $12,615

High-income $12,616 or more

Source: http://data.worldbank.org/about/country-classifications

Examples of Gross National Income

GNI,$/cap

Nor SwiUS UK Slo Por Est

Rus Bra Bot Chi Ser Bol Ind TajMoz

DRC0

20000

40000

60000

80000

100000

120000

Examples of Gross National Income (cont’d)

GNI,$/cap

Slo EstRus Bra Bot SA Chi Ser Ukr Bol Ind La

oSen Taj

Tan MozDRC

0

5000

10000

15000

20000

25000

Economic Development and InfrastructureGNI ($/pop)

Source: Queiroz and Gautam

GNI = 1.39 PRDR squared: 0.7698 countries

Abrir estradas para fazer chegaro desenvolvimento

Source: Domingo, Maputo, 3 November 2013

Road AgencyBudget

Total Road Transport Costs

User Costs

Budget, Costs $

TooLarge

Too Poor Optimal Too Good

Optimal

TooSmall

Road Condition

Optimal Road Condition

• RONET, developed by Rodrigo Archondo-Callao for SSATP, helps decision makers to:Monitor network conditionPlan allocation of resources, including

optimizing road network maintenance and rehabilitation

Assess consequences of macro policiesDesign Road Asset Management Systems

Road Network Evaluation Tools

• Availability: RONET is available free of charge on the World Bank website at: http://go.worldbank.org/HWVR0FWEF0

http://go.worldbank.org/FF0CT8M770 • General use: RONET can be used in any

city, country or region, for paved and unpaved road networks, provided that appropriate data are available

• Version 2.00 – latest version, published in 2009

Road Network Evaluation Tools

RONET Version 2.00 Road Network Evaluation Tools Version 2.00, January, 2009

Step Configuration Inputs Calculations Outputs

O-Length & Utilization1) C-Basic Configuration I-Country Data Current Condition Assessment O-Asset Value

I-Road Network Length O-RoughnessO-Network Distribution ChartsO-Network Monitoring Indicators

Performance Assessment O-Network Performance2) C-Standards Configuration I-Historical Expenditures O-Annual Work Program

O-Solution CatalogO-Road Works DistributionO-Road Works SummaryO-Historical Expenditures Comparison

3) C-Vehicle Fleet Configuration I-Road User Charges Road User Revenues O-Fuel Consumption RevenuesI-Funding Requirements O-Road User Revenues

O-Requirements & Revenues Comparison

The World BankWashington, D.C.

PAM

What is Required for an Agency to Take Advantage of Tools Such as HDM-4 and RONET?• Updated road inventory and condition data,

e.g., length of roads in each category, pavement structure, road roughness

• Traffic data, e.g., volumes by vehicle category, weight of heavy vehicles

• Road user cost data, e.g., price of new vehicles, fuel consumption and cost

• Unit cost of road works, e.g., rehabilitation ($/km), new construction ($/km)

Total 5 X 5 X 5 X 5 = 625 Road Classes

Matrix of Road Classes: Overall Network Evaluation

Network Road TypeType Concrete Asphalt S.T. Gravel EarthMotorwaysPrimarySecondaryTertiaryUnclassified

Traffic Condition CategoryCategory Very Good Good Fair Poor Very PoorTraffic ITraffic IITraffic IIITraffic IVTraffic V

Road Network Length Matrix

• Main road condition indicator used by models such as RONET and HDM

• A standard scale used throughout the world to quantify the roughness of roads

• The IRI summarizes the roughness qualities that impact vehicle response (such as vehicle vibration)

• It relates to overall vehicle ride, operating cost, dynamic wheel loads, and overall surface condition

International Roughness Index (IRI)

• The International Road Roughness Experiment, Brasilia, Brazil, 1982

• Reference: World Bank Technical Paper No. 45, “The International Road Roughness Experiment: Establishing Correlation and a Calibration Standard for Measurements,” available at: http://go.worldbank.org/0UUNR93490

Development of IRI

International Roughness Index

• IRI is determined by measuring the profile along the wheel paths of the road, and then filtering the profiles through a quarter-car mathematical model to simulate the suspension deflection of a passenger car

• Its uses include assessing road condition and as a construction specification

IRI Meaning and Uses

• “ProVAL” - Profile Viewing and AnaLysis - an engineering software used to view and analyze pavement profiles, including IRI calculations

• Sponsored by the US Federal Highway Administration (FHWA)

• Available free of charge from: http://www.roadprofile.com/

IRI Calculation from Road Profiles

22

• “RoadRuf” – a tool for computing IRI, available from the University of Michigan at: http://www.umtri.umich.edu/divisionPage.php?pageID=62

• RoadRuf includes an interactive X-Y plotter and a spectrum analyzer

• A sample program for calculating IRI is available at: http://www.umtri.umich.edu/content/IRIMain.f

IRI Calculation from Road Profiles

RONET uses simplified incremental road deterioration model for paved roads:

•traffic loading (YE4)•pavement modified structural number andsubgrade bearing capacity (SNC)•pavement age (t)•environmental coefficient (m)•existing condition (IRIa)

gm 5K m t

gp o 1 2 gm adIRI K e 1 SNC YE4 t K m IRI

RONET Paved Road Deterioration Model

• Expressed as a polynomial function of roughness for each vehicle category

• Developed using World Bank RUCKS (Road User Costs Knowledge System) model

URUC - unit road users’ cost ($/vehicle-km)IRI - pavement longitudinal roughness (m/km)a0, a1, a2, a3 - model coefficients that depend on input data

(e.g., new vehicle, fuel and tire costs)

Road User Costs Model

2 3o 1 2 3URUC a a IRI a IRI a IRI

• Very good: IRI less than 2.5 m/km• Good: IRI from 2.5 m/km to 3.5 m/km• Fair: IRI from 3.5 m/km to 5.5 m/km• Poor: IRI from 5.5 m/km to 10.5 m/km• Very poor: IRI higher than 10.5 m/km

Example of IRI and Road Condition

Riverside Freeway, SR 91, CA

32

• Five or less network types can be defined by the user based on functional classification, region, terrain type, or environmental type

Default Alternative

Configuration Configurations ExamplesNetwork Types by Types by Types by

Type Functional Class Geographic Region Terrain Type1 Motorways North Region Flat Terrain2 Primary South Region Hilly Terrain3 Secondary Easthern Region Mountainous Terrain4 Tertiary Western Region NA

5 Unclassified Central Region NA

Types of Road Network

33

• RONET uses five surface types. The country specific characteristics of the surface types are user defined

Default

Surface ConfigurationType Surface Type

1 Cement Concrete2 Asphalt Mix3 Surface Treatment4 Gravel5 Earth

Surface Types

Average Annual Daily Traffic (AADT) Illustrative Standards

Surface Traffic Traffic Minimum Maximum Average Geometry Pavement

Type Category Level (veh/day) (veh/day) (veh/day) Standard StandardEarth Traffic I T1 0 10 5 1-lane warranted Formation not warranted

Traffic II T2 10 30 20 1-lane warranted Formation warrantedTraffic III T3 30 100 65 2-lane warranted Gravel warrantedTraffic IV T4 100 300 200 2-lane warranted Gravel warrantedTraffic V T5 300 1,000 650 2-lane warranted Paved Surface warranted

Gravel Traffic I T2 10 30 20 1-lane warranted Formation warranted

Traffic II T3 30 100 65 2-lane warranted Gravel warranted

Traffic III T4 100 300 200 2-lane warranted Gravel warrantedTraffic IV T5 300 1,000 650 2-lane warranted Paved Surface warranted

Traffic V T6 1,000 3,000 2,000 2-lane warranted Paved Surface warrantedPaved Traffic I T4 100 300 200 2-lane warranted Gravel warranted

Traffic II T5 300 1,000 650 2-lane warranted Paved Surface warrantedTraffic III T6 1,000 3,000 2,000 2-lane warranted Paved Surface warrantedTraffic IV T7 3,000 10,000 6,500 2-lane warranted Paved Surface warranted

Traffic V T8 10,000 30,000 20,000 4-lane warranted Paved Surface warranted- Standard given for illustration purposes. Proper standards are country specific.- AADT of motorized 4-tires or more 2-way traffic

Traffic categories vary by surface type

35

• Very Good: requires only routine maintenance (RM)

• Good: requires RM plus preventive maintenance or spot regravelling or repairs

• Fair: requires RM plus periodic maintenance • Poor: requires RM plus strengthening or partial

reconstruction • Very Poor: requires RM plus full reconstruction

Road Condition Categories

36

• Length of road sections (per category, traffic, condition) comprising the network

• Unit cost of road works• Selected country data (e.g., discount

rate, fuel cost, salaries, vehicle fleet, traffic growth rate)

RONET Main Input Data

Road CurrentType Condition Current Asset Value Unit Cost

Paved Roads Very Good Construction Unit CostGood Construction Unit Cost - Preventive Treatment Unit Cost

Fair Construction Unit Cost - Resurfacing Unit CostPoor Construction Unit Cost - Strengthening Unit CostVery Poor Construction Unit Cost - Full Reconstruction Unit Cost

Gravel Roads Very Good Construction Unit CostGood Construction Unit Cost - Spot Regravelling Unit Cost

Fair Construction Unit Cost - Regravelling Unit Cost

Poor Construction Unit Cost - Partial Reconstruction Unit CostVery Poor Construction Unit Cost - Full Reconstruction Unit Cost

Earth Roads Very Good Construction Unit CostGood Construction Unit Cost - Spot Repairs Unit CostFair Construction Unit Cost - Heavy Grading Unit CostPoor Construction Unit Cost - Partial Reconstruction Unit CostVery Poor Construction Unit Cost - Full Reconstruction Unit Cost

Current Asset Value Calculation

Budget Scenarios ConsequencesOptimal +2 Road WorksOptimal +1 Performance FinancialOptimal Assessment EconomicOptimal -1 ConditionOptimal -2 Asset ValueOptimal -3 Road UsersDo Minimum Etc.Do NothingCustom

RoadNetwork

Performance Assessment

What are the consequences of different budget scenarios?

RONET evaluates alternative maintenance and rehabilitation road works standards for each road class

Road Work Standards

Code StandardA Very highB HighC MediumD LowE Very lowF Do minimumG Do nothing

Defined in RONET at: Capital Road Works Standards Configuration

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

0 5 10 15 20

Year

Rou

ghne

ss (I

RI,

m/k

m)

Very High StandardHigh StandardMedium StandardLow StandardVery Low StandardDo MinimumDo Nothing

Asphalt Mix Roads Standards

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

Pres

ent V

alue

Cos

ts (M

$)

Road Agency Costs Road User Costs

Total Society Costs

Optimal Standard

Least Total SocietyCosts

RONET determines optimal standard per road class

Budget ScenariosOptimal + 2 Two standards above optimal standard per road class

Optimal + 1 One standard above optimal standard per road class

Optimal Optimal standard per road class

Optimal – 1 One standard below optimal standard per road class

Optimal – 2 Two standards below optimal standard per road class

Optimal – 3 Three standards below optimal standard per road class

Do Minimum Do minimum on all road classes

Do Nothing Do nothing on all road classes

Custom User defined standard per network type and traffic category

Road Agency Costs Breakdown (Years 1-20)Annual Costs Years 1-20, M$/year

Network Scenario Rehabilitation Periodic Maint. Recurrent Maint. Road AgencyTotal Optimal +2 28.6 27.6 10.6 66.8Network Optimal +1 25.4 19.6 10.1 55.1

Optimal 19.6 18.4 7.7 45.7Optimal -1 21.5 11.2 8.1 40.8Optimal -2 17.9 10.5 8.5 36.8Optimal -3 16.1 11.9 3.4 31.4Do Minimum 6.9 8.5 2.4 17.7Do Nothing 0.0 0.0 0.0 0.0Custom 16.6 24.9 7.4 48.8

An Example of Consequencesto the Road Agency

Unit Road User CostsUnit Road User Costs ($/vehicle-km)

Network Scenario Current Years 5 Years 10 Years 20Total Optimal +2 0.328 0.298 0.298 0.296Network Optimal +1 0.328 0.299 0.301 0.306

Optimal 0.328 0.301 0.301 0.308Optimal -1 0.328 0.309 0.313 0.325Optimal -2 0.328 0.318 0.326 0.339Optimal -3 0.328 0.335 0.339 0.352Do Minimum 0.328 0.355 0.369 0.397Do Nothing 0.328 0.362 0.376 0.420Custom 0.328 0.312 0.315 0.311

Consequences to Road Users

Society Costs (Total Costs Years 1-20)Total Costs Years 1-20, M$

Network Scenario Road Agency Road Users SocietyTotal Optimal +2 1,335 17,698 19,033Network Optimal +1 1,102 17,936 19,038

Optimal 913 18,026 18,939Optimal -1 817 18,794 19,610Optimal -2 735 19,491 20,226Optimal -3 629 20,360 20,989Do Minimum 354 22,027 22,381Do Nothing 0 22,896 22,896Custom 977 18,635 19,612

Consequences to Society

0.0

5.0

10.0

15.0

20.0

25.0

Optimal +2 Optimal +1 Optimal Optimal -1 Optimal -2 Optimal -3 Do Minimum Do Nothing Custom

Scenario

Current Year 5 Year 10 Year 20

Consequences to Road Network Condition: Roughness (IRI in m/km)

RoadWorksDetails(M$)Other Tables for:($/km-year)($/veh-km)(km/year)

per surface classand surface type

Years 1-5 Years 6-20Road Agency Costs (M$/year) Road Agency Costs (M$/year)Network Paved Unpaved Total Percent Network Paved Unpaved Total PercentMotorways 0.0 0.0 0.0 0% Motorways 0.0 0.0 0.0 0%Primary 27.0 2.7 29.8 33% Primary 10.4 1.5 11.9 39%Secondary 11.1 23.0 34.1 38% Secondary 3.1 10.1 13.2 43%Tertiary 0.0 27.1 27.1 30% Tertiary 0.0 5.4 5.4 18%Total 38.2 52.9 91.0 100% Total 13.5 17.0 30.5 100%Percent 42% 58% 100% Percent 44% 56% 100%Rehabilitation Costs (M$/year) Rehabilitation Costs (M$/year)Network Paved Unpaved Total Percent Network Paved Unpaved Total PercentMotorways 0.0 0.0 0.0 0% Motorways 0.0 0.0 0.0 0%Primary 13.1 2.3 15.3 24% Primary 3.2 0.0 3.2 65%Secondary 9.2 16.7 25.9 41% Secondary 1.7 0.0 1.7 35%Tertiary 0.0 22.5 22.5 35% Tertiary 0.0 0.0 0.0 0%Total 22.2 41.5 63.7 100% Total 4.9 0.0 4.9 100%Percent 35% 65% 100% Percent 100% 0% 100%Periodic Maintenance Costs (M$/year) Periodic Maintenance Costs (M$/year)Network Paved Unpaved Total Percent Network Paved Unpaved Total PercentMotorways 0.0 0.0 0.0 0% Motorways 0.0 0.0 0.0 0%Primary 12.1 0.2 12.2 63% Primary 5.4 1.2 6.5 36%Secondary 1.4 3.0 4.4 22% Secondary 0.9 6.8 7.7 43%Tertiary 0.0 2.9 2.9 15% Tertiary 0.0 3.8 3.8 21%Total 13.4 6.1 19.6 100% Total 6.2 11.8 18.0 100%Percent 69% 31% 100% Percent 35% 65% 100%Recurrent Maintenance Costs (M$/year) Recurrent Maintenance Costs (M$/year)Network Paved Unpaved Total Percent Network Paved Unpaved Total PercentMotorways 0.0 0.0 0.0 0% Motorways 0.0 0.0 0.0 0%Primary 1.9 0.3 2.2 28% Primary 1.9 0.3 2.1 28%Secondary 0.5 3.3 3.8 50% Secondary 0.5 3.3 3.8 50%Tertiary 0.0 1.7 1.7 22% Tertiary 0.0 1.7 1.7 22%Total 2.5 5.2 7.7 100% Total 2.4 5.2 7.6 100%Percent 32% 68% 100% Percent 31% 69% 100%

Road User Charges

Road User ChargesPerformance Assessment Fuel Consumption

Vehicle Registration FeesLicense FeesRoad Damage Fees

Routine Maintenance Distance Travel FeesPeriodic Maintenance International Transit Revenues

Rehabilitation Toll Revenues+ Foreign Vehicle Permit Revenues

Administration Vignettes RevenuesImprovements Carbon Taxes Revenues

Other Traffic Enforcement Revenues= Other Fees and Taxes Revenues

Total Funding Needs Total Revenues

Funding Gap

• Review RONET’s User Guide• RONET familiarization interactive

exercise• Obtain as realistic as possible

information on a road network of each participating country

• Develop an optimum road network M&R program for the selected network

• Prepare a brief report and present the results

Next steps

Cesar QueirozSSATP/World Bank ConsultantFormer World Bank Highways AdviserTel +1 301 755 7591queiroz.cesar@gmail.comWashington, DC, USA

RONET Team ExerciseRoad Network Two-lane Equivalent:Length, condition and traffic levels

Length, kmPrimary Good Fair Poor Good Fair Poor

5000 1000 2500 1500

Asphalt 300 750 450 Surf Treat 700 1750 1050vpd300-1000 60 150 90 140 350 2101000-3000 240 600 360 560 1400 840

This example of calculation is for primary roads. Please follow the example and obtain the lengths

per cell for secondary and tertiary roads.

Cesar Queiroz, former World Bank Highways Adviser, is an international consultant on roads and transport infrastructure. His main expertise is in public-private partnerships, road management and development, performance-based contracts, port reform and rehabilitation, improving governance, quality assurance and evaluation, research, teaching and training. Between 1986 and 2006, he held several positions with the World Bank, including Lead Highway Engineer and Principal Highway Engineer. Prior to joining the World Bank, Cesar was the deputy director of the Brazilian Road Research Institute in Rio de Janeiro. He holds a Ph.D. in civil engineering from the University of Texas at Austin, a M.Sc. in production engineering from the Federal University of Rio de Janeiro, and a B.Sc. in civil engineering from the Federal University of Juiz de Fora, Brazil. Cesar has published two books and more than 130 papers and articles. His recent assignments include infrastructure advisory services to Russia, Brazil, Latvia, Lithuania, Poland, Ukraine, Philippines, Uganda, Sri Lanka, India, Egypt, Colombia, Laos, Mozambique, Saudi Arabia, Tunisia, Sweden and Norway. He is currently a visiting professor at the University of Belgrade, Serbia, and has lectured on PPP at George Washington University since 1996, and at the International Law Institute since 2007.