Evaluation of Maintenance Activities in Terms of Chile's Road Infrastructure Asset Value

8/3/2019 Evaluation of Maintenance Activities in Terms of Chile's Road Infrastructure Asset Value

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Evaluation Of Maintenance Activities InTerms Of Chiles Road Infrastructure

Asset Valuede Solminihac, H. E.P.E., MSc, PhD, Professor, School of Engineering, Pontificia Universidad Catlica, Santiago, Chile

Hidalgo, P.P.E., MSc, Project Manager, APSA Infrastructure Management, Santiago, Chile

Rojas, P.P.E., MSc, Research Assistant, School of Engineering, Pontificia Universidad Catlica, Santiago, Chile

Bustos, M.

P.E., PhD, Post-Doctorate Researcher, project MECESUP PUC 9903, School of EngineeringPontificia Universidad Catlica, Santiago, Chile

SYNOPSIS

Road infrastructure maintenance affects the future performance of roads and can increase or diminish roadasset value over time, depending on the efficiency and timeliness of the applied maintenance policies. Theaim of this paper is to propose a methodology to evaluate the cost-effectiveness of maintenance plansapplied along a multiyear lapse over a network, in terms of the networks asset value that is obtained at theend of the evaluation period.

As an application of such methodology, the 1.3 version of the HDM4 model, calibrated to local conditions,

was used to evaluate the performance of the complete network of national public roads in Chile, using a setof characteristic road sections over a 20-year time span. Different maintenance policies were defined and theIRI minimization criteria was used, under the assumption that a lower IRI for the road network implies ahigher asset value. Three investment levels were considered: a minimum level; a maximum level, thatassumes limitless funding; and a medium level, corresponding to an average budget between the minimumand maximum levels.

Relationships very close to linear were found between final asset value after 20 years, and thecorresponding investment amounts, both for the paved and unpaved sub-networks, and also for the wholenetwork. The results also showed that very high levels of investment are necessary to obtain a smallincrease in asset value.

Nevertheless, most of such investment is applied to routine or periodic maintenance, that is essential to

maintain pavements in good conditions along time, but do not make significant variations of the asset value.It shows that the variation of asset value on its own is not a good variable to judge appropriately theconvenience of maintenance policies. To optimize such polices it is therefore essential to consider also thesocial costs and benefits related to each maintenance policy.

6th International Conference on Managing Pavements (2004)

TRB Committee AFD10 on Pavement Management Systems is providing the information contained herein for use by individual practitionersin state and local transportation agencies, researchers in academic institutions, and other members of the transportation researchcommunity. The information in this paper was taken directly from the submission of the author(s).


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INTRODUCTION

Transportation infrastructure is an essential factor for the development of a country. An adequateinfrastructure, according to the real needs of the country, and in a good overall condition, can make asignificant contribution to the progress of the community. Thus, it is very important to make appropriatevaluations of the nations roads asset, and to develop mechanisms to enhance the road infrastructure and to

maintain it in optimal service conditions.

Developed countries are currently incorporating new procedures of management and valuation to theinfrastructure asset of the society, and such procedures are known by the generic name of AssetManagement (U.S. Department of Transportation, 1999). Such methodologies are aimed to supervise thewhole transportation system and to optimize the strategies of maintenance and replacement of theinfrastructure components, following an effective management of costs and resource allocation. Assetmanagement is considered an strategic way, more than tactic, to administrate the infrastructure patrimony,taking into account budgetary restrictions.

ObjectivesThe main purpose of this study was to develop and apply an evaluation methodology for road maintenanceprograms, aimed to analyze the convenience of such programs from the perspective of their impact in the

road asset value. According to this, the information obtained can be used to provide the upper roadmanagement levels with a tool to elaborate a long-term strategic plan, considering the incidence of thoseplans on the evolution of the value of the whole road patrimony.

Afterwards, such methodology was applied to the evaluate a set of maintenance policies for the nationalroad network of Chile that is not currently under private concession, considering both paved and unpavedroads, from the viewpoint of the evolution of the road asset value.

METHODOLOGY TO DETERMINE ASSET VALUE OF A ROAD NETWORK

Global Description Of The MethodologyBasically, the evaluation methodology follows the next steps:

a) Classification of road network pavements: from inventory data, a distribution of the road networkpavements into different classes is made, according to the following parameters that allow to definethe factorial analysis:

Road category: according to the relative importance of the roads Road surface type: paved or unpaved Road surface condition: characterized by qualitative indicators (good, fair, poor, etc.), associated to

specific distress values. Pavement type: asphalt (with various sub-types) and concrete pavements Geographic zone: represents different climatic conditions. Traffic: Annual Average Daily Traffic (AADT), growth rate, vehicle types distribution, etc.

b) Determination of the Initial Asset Value of the road infrastructure: from the initial condition of the roadnetwork, already classified into representative links according to the analysis factorial, the assetvalue of those links is calculated as it is explained later, to have a basis to compare the variation ofthe asset value during the evaluation process

c) Definition of maintenance and rehabilitation (M&R) activities for the road network: taking into accountthe practices usually carried on by the road administration agency, the construction, maintenanceand rehabilitation policies to be evaluated are established, associated to threshold and applicationconditions. Other M&R practices can also be evaluated, if enough experience about theirapplicability is available for the agency.

d) Performance modeling for the representative pavements: for each combination included in theanalysis factorial, the evolution of the respective pavement performance is modeled along a

predefined evaluation period. The effect of calibration factors, and the M&R strategies defined in theprevious step, are also considered in this process. This specific methodology uses the World Banks




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program HDM-4, Highway Development and Management (Kerali, 2000) as the main evaluation andmodeling tool. HDM-4 models should be calibrated to local conditions.

e) Optimization of M&R policies: considering the results of the evaluation, the strategy that permits toobtain the best infrastructure condition is determined for each case. Using HDM-4, it can be done byan internal algorithm designed to determine which M&R strategy maximizes the ride quality of thepavement for each case, by minimization of the roughness values (expressed as InternationalRoughness Index, IRI) at the end of the evaluation term.

f) Consideration of budget constraints: taking into account the availability of financial resources,defined through budgetary levels, a program of activities is defined for each budget level. At the endof the evaluation process, economic results and the structural and functional condition of eachrepresentative link are obtained for the different budgetary scenarios.

g) Extrapolation of the results to the whole road network: the individual results for the representativelinks are extrapolated to the whole extension of the road network, obtaining as a final result the assetvalue of the complete road network, for each budgetary level.

A schema of the described methodology is presented in Figure 1.

Figure 1 Methodology to analyze the asset value of a road network

APPLICATION TO THE ANALYSIS OF THE STATE ROAD NETWORK IN CHILE

The methodology outlined above was applied to the evaluation of the Chilean national road network,considering only paved or unpaved roads not under private concession. Such evaluation was part of a morecomprehensive study aimed to determine the asset value for various components of public infrastructure (notunder private concession) in Chile (Artigas et al., 2003). Information about inventory, traffic and currentcondition used in the road network evaluation was provided by the Ministry of Public Works of Chile.

Table 1 summarizes the amount of kilometers of roads evaluated in this study, and which are their respectivepercentage of representation with respect of the complete road network not under concession in Chile.

Road Inventory

Typical Structuresin each zone

Pavement ConditionClasses for each zone

IRIBibliographyVisual Inspection

M&R PoliciesConsidered

Performance Modeling bystructure, category andzoneTraffic

Calibration Factors

Optimal M&R policies foreach representative structure

Whole network extrapolation

Budget levels

Final Asset Value, for eachbudgetary scenario

Definition of Geographic Zones

Final condition ofrepresentative structures




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Table 1 Representativity of the Chilean road network under evaluation (Artigas et al., 2003)

NetworkKm.

EvaluatedTotal amount Km.Not concessioned

Representativity ofEvaluated Network

Paved Roads 14.041 15.330 (*) 92%

Unpaved Roads 61.142 63.548 96%(*) According to 2001 Road Inventory, DNV Chile

Road Network Classification By Geographic ZonesFirst of all, the information available about road inventory, traffic and climatic data, current structural andfunctional condition of the roads, unitary prices for M&R activities, etc., was analyzed and processed toconstitute the study database. Four geographic zones were considered for Chile, comprising the followingadministrative regions of the country in each case:

North Zone: Regions I to IV Central Zone: Regions I to VII, and the Metropolitan Region South Zone: Regions VIII to X Austral Zone: Regions XI and XII

That was done with the purpose of dividing the road network into a number of zones that permit to reach astrategic level of detail in the results, optimizing the resources allocated to this kind of analysis. In Chile, theclimatic characteristics show a simultaneous decrease of average temperatures and increase of annualprecipitations, when traveling from north to south. Figure 2 shows the zones defined above in a map of Chile,and also representative pictures of landscapes and roads pertaining to different zones.

Figure 2 Geographic zones considered for Chile, and examples of roads and landscapes of each one




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Representative Road Structures By ZoneFor each zone, representative structures were defined considering the different types of roads that exist(asphalt mix pavements, double treatments, concrete pavements, gravel roads, etc.), from the inventorydata. To obtain the representative structures for paved roads in each zone, the procedure described belowwas followed:

a) Inside each zone, the roads were classified by surface type, thus obtaining the different surface

types that exist, and the amount of kilometers of each type. The different road categories of theNational Road Network of Chile were also considered, distributed in Basic Road Network (roadclasses A, B and C), Primary County Road Network (D class), and Secondary County Road Network(E class), as shown in Table 2.

Table 2 Road Categories in Chile (Almonte 1999)

ROAD CATEGORIES CHARACTERSTICSClass A National RoadsClass B Primary Regional RoadsClass C Secondary Regional RoadsClass D Primary County RoadsClass E Secondary County Roads

b) Roads were then distributed by structure types for each zone. As a first approximation, therepresentative pavement for each structure type was obtained by a calculation a weighed average oflayer thickness, construction year, intervention year and soil types, depending on the road length.

c) In the case that the data from pavements show high variation, the representative structures weresubdivided to obtain averages whit lower variation. The final representative structures to be used inthe evaluation were thus obtained, taking into account that at least an 80% of the zonal road networkwas adequately represented by such structures.

To control the dispersion of the structural characteristics, in the case of asphalt pavements the variationcoefficients (average divided by standard deviation) were verified both for modified structural number (SNC),

a parameter that was calculated as defined in HDM-III (Watanatada et al, 1987), and for the surface layerthickness. In concrete pavements, the variability of slab thickness was controlled. For all cases, the variationcoefficients were lower than 50%, and most of them were lower than 20%, showing a very controlleddispersion for the representative structures. In the case of unpaved roads, a similar procedure was followed,as described below:

a) Road links were classified by geographic zone (4 zones), type of road surface (gravel or earth) andsurface condition (good, fair or poor).

b) Representative structures were then obtained for each class, by the calculation of a weighedaverage of geometric characteristics, road layer and soil properties, etc., that considers the length ofroad links included into each class. It allowed to obtain 24 representative structures for unpavedroads (4 x 2 x 3 = 24).

Definition Of Analysis Factorial For The StudyA factorial table was then developed considering all the combinations of zones, road types and surfacecondition. This factorial is shown in Table 3, where 60 possible combinations of zone, structure and condition(G, F, P, respectively good, fair and poor), could be evaluated in the study.

Definition Of Surface Condition Indicators And Traffic AssignmentsFunctional and structural condition of the representative pavements was defined as a first approach followingthe National Roads Administration of Chile (Direccion Nacional de Vialidad, DNV) criteria, which establishesthree levels: Good (G), Fair (F) and Poor (P). Such criteria assigns road condition according to themaintenance or rehabilitation needs of the road. Maintenance categories for paved roads, both asphalt andconcrete, are grouped as follows:

Routine Maintenance: comprises all the operations that must be carried on along the year,independently of the climate or traffic level, as drainage and shoulder maintenance, reposition ofroad signs, earth works for slope maintenance, etc.




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Periodic Maintenance: includes preventative maintenance activities, applied periodically in lapseslonger than one year

Major Maintenance or Rehabilitation: corresponds to those works that make significantimprovements in structural and functional condition of the pavement, as structural overlays orreconstructions.

According to these definitions, the different condition levels are defined as follows:

Good Condition: includes all roads that only require routine maintenance Fair Condition: comprises the roads that require periodic maintenance, as preventative or corrective

operations, to give an adequate level of service. Poor condition: it corresponds to all those roads that need major maintenance or rehabilitation

Table 3 Factorial design of combinations to be evaluated (Artigas et al., 2003)

Zone North Central

Structure Types HMA CDA DAT GRV Earth HMA DAT CON IRF GRV Earth

Condition G F P G F P G F P G F P G F P G F P G F P G F P G F P G F P G F P

Zone South AustralStructure Types HMA DAT CON GRV Earth CON HMA GRV Earth

Condition G F P G F P G F P G F P G F P G F P G F P G F P G F P

HMA: Hot Dense Asphalt MixCDA: Cold Dense Asphalt MixDAT: Double Asphalt TreatmentIRF: Surface Imprimation ReinforcedCON: Concrete PavementsGRV: Unpaved Gravel Roads

The proportion of roads in good, fair or poor condition, by zone and structure type, was obtained in this

specific case from the data provided by the Road Management Department of the DNV (Departamento deGestin Vial, 2002b).

A similar procedure of averages weighed by road length was followed to characterize the representativerange of distress for each condition level, by structure type and zone. Besides IRI, other distress wereconsidered, such as cracking, rutting, potholes and raveling in asphalt pavements; transverse joints faultingand slab cracking for concrete pavements; and age and thickness of the gravel surface layer for unpavedgravel roads. For earth roads, only IRI was used to define condition levels. Those average values of distress,weighed by road length, were used as indicators of initial road condition for the process of modeling theperformance of each representative structure in each geographic zone.

With respect to the traffic that would be traveling along the representative roads during the evaluation period,an specific value of AADT and vehicle distribution was associated to each typified structure in each zone,

and an annual growth rate that only changes between paved and unpaved road networks was used. Theinitial AADT values and vehicle distribution were again obtained as weighed averages, from data provided bythe Traffic Census 2000 made by the DNV of Chile.

Annual growth rates were estimated from values that are typically used for social evaluations of road projectsin Chile. In Table 4 there are shown, as examples, the values adopted for initial AADT, distribution of vehicletypes, and annual growth rates, for the representative structures of paved roads, by geographic zone.

Maintenance And Rehabilitation StrategiesA maintenance policy or strategy is a set of maintenance activities, joined to their respective applicationthreshold, logically related between them, that are applied according to road surface type and condition.Such policies were designed, for this study, from the M&R activities typically used by DNV of Chile, with theircorresponding unit costs, not only economic (social costs) but also financial (private or market costs). The

main guidelines that helped to define the M&R strategies are shown in Table 5.




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Table 4 Traffic data adopted forpaved road network analysis (Artigas et al., 2003)

Vehcle Types DistributionZone

TipifiedStructure

InitialAADT Cars Pick ups Simple Trucks Truck > 2 axles Buses

HMA 744 31.7% 27.9% 10.3% 22.6% 7.6%

North CDA 666 31.7% 27.9% 10.3% 22.6% 7.6%

DAT 944 31.7% 27.9% 10.3% 22.6% 7.6%HMA 2479 39.7% 31.1% 10.8% 11.4% 7.0%

Central DAT 2241 39.7% 31.1% 10.8% 11.4% 7.0%

CON 6017 41.3% 28.2% 10.0% 12.0% 8.5%

IRF 372 37.9% 35.6% 16.0% 5.8% 4.6%

HMA 2099 36.6% 32.8% 11.8% 10.6% 8.2%

South DAT 1564 36.6% 32.8% 11.8% 10.6% 8.2%

CON 3806 38.9% 27.0% 10.9% 14.5% 8.8%

CON 811 32.2% 29.4% 9.6% 18.1% 10.6%Austral HMA 471 30.7% 39.3% 11.8% 8.9% 9.2%

Annual traffic growth 6.0% 5.5% 4.0% 4.0% 4.0%

From guidelines shown in Table 5, a set of M&R policies was elaborated, to be analyzed for eachrepresentative structure, corresponding 28 strategies for asphalt pavements, 18 for concrete pavements and17 for unpaved roads.

Table 5 Guidelines to define maintenance activities, depending on road surface (Almonte, 1999)

Road Surface Condition Recomended ActivityGood Routine Maintenance and/or seals

Asphalt Fair Structural OverlaysPoor Reconstruction

Good Routine MaintenanceConcrete Fair Slab replacement, joint and crack sealing, etc.

Poor ReconstructionGood Routine Maintenance

DAT or IRF Fair Surface TreatmentsPoor ReconstructionGood Routine Maintenance

Gravel Fair Surface gravel repositionPoor ReconstructionGood Routine Maintenance

Earth Fair Drainage Rehabilitation and surface cleaningPoor Construction or reconstruction basic works

Determination Of Initial Asset Value Of The Road Network

Conceptually, the initial value of road infrastructure is defined as the sum of the individual values for eachroad link in its current condition, taking into account the loss of value due to distress in those pavements thatshow a condition lower than a new pavement condition. In this study, the Initial Asset Value of therepresentative structures was calculated from data of initial condition of the road network, obtained from theRoad Inventory 2001 developed by the DNV of Chile. The calculation procedure was adapted form themethodology developed by Almonte (1999), following recommendations elaborated by CEPAL (Schliesserand Bull, 1992). The procedure has the following steps:

a) Input Data: information about inventory (road class, length, surface type, soil and terrain type, etc.),condition data, and data of costs for construction and M&R activities.

b) Calculation of the New Road Value: it corresponds to the construction value of the representativeroad under analysis. Thus, the asset value for a new road is calculated as the cost due to




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construction of the road, including all the layers, and the necessary complementary works. Thisvalue is also known as the Maximum Theoretical Value, and it is determined from the workquantities, which depend on the road surface type, road class and topography (level, ondulating ormountain road). At network level, the Maximum Theoretical Value corresponds to the value of thewhole infrastructure if all the roads were recently built or in a good condition. To estimate such value,in the present study there were estimated average values for work quantities and their respectivecosts, weighed by distribution of the roads according topographic conditions.

c) Determination of Distress Value: it consists on the cost associated to the activities required to keep aroad from a distressed condition, to a good or new pavement condition. It obviously depends on theinitial condition of the road, because such condition defines the M&R activities to be applied. In thisstudy, the costs and work quantities to keep the road to an optimal condition were estimatedaccording the guidelines described in Table 5.

d) Calculation of Current Road Asset Value: for each representative structure, the current value isobtained through the difference between the New Road Value and the Distress Value. Repeatingsuch calculation for all the representative structures, and extrapolating the results for the whole roadnetwork, the current road asset value is obtained for the complete network, and it would serve as acomparative basis for the economic evaluation.

Applying the described procedure, the current asset value was determined for the Chilean road infrastructurethat is not under private concession, for year 2001. Table 6 show the current values obtained for paved andunpaved roads, considering the different geographic zones. Results from Table 6 show that initial assetvalue for the whole road infrastructure not under concession is 9364.54 million dollars. The paved roadnetwork represents less than one-third of such value.

Table 6 Current Asset Value for the road infrastructure not concessioned in Chile (2001)

ZonePaved Network(Millions US$)

Unpaved Network(Millions US$)

Complete Network(Millions US$)

North 1019.88 2018.07 3037.94

Central 757.12 1399.46 2156.58

South 868.82 2516.92 3385.74

Austral 285.16 499.11 784.27

Total Country 2930.98 6433.56 9364.54

US$= 650 ch$

Evaluation Of Road Network Performance Under Different Budgetary ScenariosAfterwards, the performance of the representative structures shown in Table 3 for each zone was modeled,along a 20-year evaluation period. The version 1.3 of the computational program HDM-4 was used for thatpurpose, adjusted to local conditions with calibration factors provided by previous studies (de Solminihac etal, 2002, 2002b and 2003)

The specific objective of the evaluation was to determine which would be the best global standard for thenetwork, measured in terms of minimizing roughness IRI, considering three alternatives of resource

availability. Such consideration is based on the assumption that as the road condition improves (meaningless IRI and distress values), the road asset value increases. The software HDM-4 has a subroutine thatallows to define a program of activities at network level by minimization of an objective function, and one ofthe alternative functions included in the current version of the software is roughness IRI. The final conditionobtained for the representative structures allows to calculate the final road asset value, and to analyze itsvariation along time.

Three budgetary levels were defined for the analysis of the national road network, being the budget with norestrictions considered as the maximum level, and the medium budget as the average between maximumand minimum. The minimum budget was defined from estimations of costs for maintenance policies basedmainly on periodic and routine activities. Maximum budget was determined after initial modeling with HDM-4,under the premise of IRI minimization for each representative structure, but supposing unlimited availabilityof funds. The global monetary quantities of each budgetary level are defined below:

Minimum Budget: 4432.8 millions US$




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Medium Budget: 10055.1 millions US$ Maximum Budget: 15718.1 millions US$

Table 7 shows the criteria used to establish the distress limits between good, fair and poor condition, duringthe road network evaluation stage, for different distress indicators, considering the different road types.

Table 7 Criteria used to define condition levels according distress levels

TYPE OF

STRUCTURE Good Fair Poor

< 3.5 3.5 - 5.5 > 5.5

ASPHALT < 10 10 - 30 > 30

0 0 - 2 > 2

< 3.5 3.5 - 5.5 > 5.5

CONCRETE < 15 15 - 30 > 30

< 6 6 - 10 > 10

< 10 10 - 15 > 15

> 100 20 - 100 < 20

North Zone < 10 10 - 15 > 15

IRI Central Zone < 10 10 - 15 > 15

(m/km) South Zone N/A < 15 > 15

Austral Zone N/A < 15 > 15

N/A: For that geographic zones, with frequent precipitations and low temperatures

usually the earth roads are not able to show good condition

GRAVELIRI (m/km)

Gravel Thickness (mm)

EARTH

CONDITIONINDICATOR

IRI (m/km)

% Cracking

DISTRESS

Potholes

IRI (m/km)

% Cracking

Joint Faulting

According to the criteria presented in Table 7, each representative structure has a final condition (good, fairor poor) at the end of the evaluation lapse. Applying the concept of Distress Value, the Final Road AssetValue can be calculated, for each different budgetary level.

ANALYSIS OF RESULTS OF THE EVALUATION

Variation Of Global Network Condition Along The Evaluation PeriodFigures 3 to 5 show the average evolution of IRI along the evaluation period, respective for the asphalt,concrete and unpaved roads networks, under the three budgetary scenarios previously defined, plus thewithout maintenance scenario.

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Year

IRI(m

/km)

Maximum Budget Minimum Budget

Medium Budget No maintenance

Figure 3 Evolution of average IRI for the asphalt roads network

As it would be expected, for all the cases the maximum budget allows to obtain the lowest average IRIvalues along the evaluation period. For other side, the option without maintenance shows at the end of the




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evaluation period a very bad average condition, both for asphalt (Fig. 3) and unpaved roads (Fig. 5), and afair condition for concrete roads (Fig. 4).

In the case of asphalt pavements, a medium budget is able to preserve the road network with a good to fairaverage condition (Fig. 3), according to the criteria defined by Table 7. With minimum budget, instead, fewyears after the beginning of the evaluation the asphalt road network reaches a poor condition, that stayspoor until the end of the analysis period.

With respect to the concrete pavements, Figure 4 shows that the three main budget levels (maximum tominimum) do not make important differences in global condition of the network. A minimum budget allows tomaintain the concrete roads network with a good condition along the evaluation period, reaching a faircondition only in the last years.

Finally, Figure 5 shows that the average condition of unpaved roads remains good with a maximum budget,varies between good and fair with medium budget, and the minimum budget is only able to maintainunpaved roads in a fair condition, along the evaluation lapse. It should be highlighted that between years2009 and 2010, many unpaved roads upgrade their standard as being paved with double asphalt treatments.

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IRI(m/km



Figure 4 Evolution of average IRI for the concrete roads network

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Figure 5 Evolution of average IRI for unpaved roads network




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Evaluation Of Economic ResultsThe main asset values for the complete non-concessioned road network and its sub-networks, afterextrapolation of results obtained for representative structures, are shown in Table 8.

Table 8 Variation of road asset values according budgetary levels

Road Asset Network

Final Values (MM US$)

Unpaved

Roads

Upgraded

(*)

Paved

Roads

Total

National

20 years

InvestmentInitial Value 6434 - 2931 9365

Value without maintenance 4861 - 1800 6660 0With Minimum Budget 5734 52 2685 8471 4433With Medium Budget 3690 2913 2827 9430 10055

With Maximum Budget 2139 5080 3410 10629 15718US$ = 650 ch$(*) originally unpaved roads, that upgrade their standard to paved roads during the evaluation period

When comparing the variation of the final road network asset value as the availability of resources changes,as shown in Figure 6, it seems that the minimum budget produces a loss in the asset value of approximately

10%, the medium budget allows to maintain the asset value almost equivalent to the initial value, and if thereare not budgetary restrictions the asset value increases 14%, in all cases after a 20 year evaluation period.The most critical situation happens in the without maintenance case, where the asset value decreases upto 30% with respect to its original value.

100%

71%

90%

101%

114%

0%

20%

40%

60%

80%

100%

120%

RoadAssetVa

lueComparison

Initial Asset Value Value without maintenance

Value with Minimum Budget Value with Medium Budget

Value without Budget Constraints

Figure 6 Variation of road asset value after 20 years, according to budgetary levels

It is also feasible to see how the proportion of asset value defined by the paved road network increases asthe resource availability augments (Fig. 7). It is caused mainly by the standard upgrade of many roadsoriginally unpaved, which can be done only with enough funding resources.

Another point that should be highlighted is the relationship between the magnitude of investment inmaintenance, and the road asset value at the end of the analysis period. From data provided by Tables 6and 8, the correlation between investment and asset value finally obtained, separately for the whole roadnetwork and for the paved and unpaved networks, considering the different levels of budgetary constraints.

To make this calculation, the paved road network considered included only those roads originally paved atthe beginning of the evaluation. The upgraded roads, paved during the evaluation period, were consideredas part of the unpaved network, because the upgrade investment was made on this network. Table 9 shows

the calculated values of investment and asset value for each one of the networks defined above.




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0

2000

4000

6000

8000

10000

12000

Initial Value No Maint.

Value

Minimum

Budget

Medium

Budget

Maximum

Budget

RoadNetworkAss

etValue(MMU

S$)

Unpaved Roads Paved Roads

Figure 7 Variation of the proportion of asset value corresponding to paved and unpaved road

networks, under different budgetary scenarios

Table 9 Relationship between Investment and Final Road Network Asset Value

BudgetaryLevels INV FAV INV FAV INV FAV

No maintenance 0 1800 0 4861 0 6660Minimum Budget 2202.29 2685 2230.51 5786 4433 8471Medium Budget 3327.34 2827 6727.74 6603 10055 9430Maximum Budget 4471.97 3410 11246.1 7219 15718 10629

Values in millions US$

INV: Investment FAV: Final Asset Value

Paved Network Unpaved Network Whole Network

Figure 8 shows a graph containing the corresponding values of investment and final asset value shown byTable 9. The relationship seems to be very close to linear for the three analyzed networks, as shown by therespective straight tendency lines plotted in the graph. It results very useful to determine in a more direct waythe impact of the investment amount on the asset value predicted after 20 years, considering that bothparameters seem to be linearly correlated, at least according to the results obtained in this study.

0

2000

4000

6000

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12000

14000

16000

0 5000 10000 15000 20000

Investment in Maintenance (MM US$)

FinalRoadNetworkAssetV

alue(MMU

S$)

Whole Network

Unpaved Network

Paved Network

Figure 8 Relationship between maintenance investment and final road networks asset value




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Starting from the asset value obtained for the scenario without maintenance, which is obviously the worstcase and means investment equal to zero, the results show that if an increment of 1 dollar in the asset valuewants to be obtained after 20 years, it is necessary to invest between 3 to 5 dollars in maintenance,depending on the road network considered. Approximately, the relationship between investment amount andincrement of the final asset value, from its minimum possible value without maintenance, is 3 to 1 for thepaved roads network, 5 to 1 for the unpaved network and 4 to 1 for the whole network.

This kind of simple relationships are very useful to analyze the road management policies in the upperdecision levels, taking into account the impact of those policies on the final road asset value. If a linear modelis developed from the data, as can be easily done, the resultant asset value can be calculated from any levelof investment. As an example, the linear model developed in this specific case to correlate investment andasset value, for the whole network, was the following:

FAV = 0.2412 INV + 6976 (1)(R

2= 0.9643 ; SE = 387.97)

where FAV means Final Asset Value, and INV means Investment, both values in million dollars. Applying thismodel, to maintain constant the initial asset value (equal to 9365 MM US$, as shown in Table 6) at the endof the evaluation period, the investment required is 9234.8 MM US$, very close to the value of the mediumbudget level, as it would be expected.

Similar models can be also developed for paved and unpaved road networks, but all these models have thelimitation that they were developed under very specific considerations, for an evaluation period of 20 years.The incidence of the length of evaluation lapse must be determined to propose more comprehensive models,and in any case, these models would only be applied to the specific conditions of the Chilean road network,not including roads under private concession. But they can help quite a bit to obtain quickly an estimation ofthe final asset value for any investment amount, or conversely.

At a first sight, when the relationships obtained above are analyzed, the investment in maintenance seems tobe very high when compared against the variation in asset value. It is caused by the strong incidence ofroutine and periodic maintenance over the whole asset value, considering that such activities consume highamounts of resources, and produce little or insignificant variation in the asset value of a road. This is morenotorious in the case of unpaved roads. Only the major maintenance or upgrade activities (rehabilitation,

reconstruction or new construction) can incorporate an improvement in the asset value that can bequantitatively similar to the corresponding investment amount, if the asset valuation methodology proposedin this study is followed.

These considerations also shown one of the most important limitations of the asset value as a roadmanagement tool. From the exclusive point of view of the final asset value, consequently, routine or periodicmaintenance activities would not bring significant benefits, because they are not able to produce sensibleincrements on the asset value. Such affirmation contradicts all the experience obtained during the lastdecades, which recommends the application of low-cost preventative or corrective maintenance activities,before the initiation of intensive deterioration processes in the roads that would lead to major maintenanceactivities.

It clearly indicates that the asset value by its own is not an appropriate tool to optimize maintenance policies

at network or project level, because the methodology to determine asset value does not take into accountthe transportation costs of the road infrastructure users. Vehicle operation costs and time travel costs, whoare very influenced by IRI of the road surface, environmental pollution costs, safety costs, etc., all them havehuge incidence on the social benefits of maintenance policies. Asset valuation does not consider, then, thesocial benefits generated by an overall good condition of the road network. Such benefits are essential tomake an adequate evaluation of global costs and to optimize the maintenance activities to be applied in aroad network.

Asset valuation procedures are very convenient instead to quantify, in terms of monetary units, the value of akey infrastructure such as the road network, which has a huge importance in the development of a country.From an specific initial asset value, the state administration agency, or the private if the road is underconcession, can evaluate the incidence of many different maintenance policies on such value, consideringmany budgetary scenarios.

More than an optimization tool, asset valuation is a control tool for maintenance policies. And if thegovernment wish to transfer to the private the management of a road, or the private which has a concession




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evaluates the possibility to continue, abandon or transfer the management business, the asset valuationbecomes a very appropriate methodology to have a real idea of the actual value of such infrastructure. Thisallows to reduce the margin of uncertainty about that value, and therefore to make more trustable andprecise analysis of the business involved, both for the government and for the private enterprises.

CONCLUSIONS AND RECOMMENDATIONS

The development of economic evaluation techniques applied to infrastructure management, as assetvaluation procedures, help the governments to take more efficient decisions, based on innovative decisiontools. Current tendencies show the importance and convenience to manage the state infrastructure as aprivate enterprise would do with its patrimony, considering long-term evaluations, taking into account benefitsand costs, and analyzing how the different possible management strategies can increase or decrease thevalue of that patrimony owned by the community.

For the analysis of road infrastructure, the consideration of age, useful life and condition of the roads at themoment to evaluate the road asset value, makes it possible to develop a methodology to obtain an adjustedand realistic value of the road infrastructure. Such methodology was developed in this study, and applied todetermination of the road network asset value for Chile, considering only paved and unpaved national roadsthat are not currently under concession.

The analysis of the variation of the road network asset value according to different budgetary scenariosdemonstrated the usefulness of the asset valuation as a tool to evaluate maintenance policies in the longterm. Results obtained from this study show that there seems to be direct relationships, almost linear,between the amount of road investment and final asset value at the end of the analysis period. Suchrelationships can be very helpful to make quick and simplified estimations of the impact of differentinvestment amounts over the road asset value.

Besides, the possibility to quantify appropriately the value of an specific road infrastructure allows to developa more precise and trustable evaluation of the business involved in the potential concession of suchinfrastructure, both for the government and the private enterprises.

Nevertheless, the results of this study also permitted to conclude that asset valuation by its own is not a goodtool to optimize the allocation of resources, thus it is important to consider, in order to achieve that

optimization, the social costs and benefits associated to each investment strategy, especially vehicleoperating costs and travel time costs.

Finally, the following recommendations can be suggested, in the light of the results obtained in this study:

More assessments should be made using different analysis periods, to verify the actual incidence ofperiod length on the results of the study

Further research should also be made, incorporating the economic evaluation of the network fromthe social point of view. The optimal policies should be determined after considering transport andother social costs, and the final asset value obtained after the application of those policies wouldthen be compared with the results of this study, where only and infrastructure condition optimizationthrough IRI minimization was developed.

It is also recommended that the Ministry of Public Works of Chile should develop regional databases

for costs and work quantities of the maintenance activities. It would allow to make more precise andrealistic evaluations at regional level, incorporating the main variations that exist for those itemsbetween different regions.

REFERENCES

Almonte, L. (1999). Valorizacin del Patrimonio Vial. Thesis for applying to Civil Engineer degree.Universidad de Chile, Santiago, Chile.

Artigas J., de Solminihac H., Rudolphy S., Varas E. (2003) Levantamiento, Catastro y valoracin delPatrimonio de Infraestructura de Chile Etapa II. Facultad de Ciencias Econmicas y Administrativas.Pontificia Universidad Catlica. Direccin de Planeamiento. Ministry of Public Works of Chile. September2003, Santiago, Chile.




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de Solminihac H., Hidalgo P, Salgado M, Valdes M. (2002) Calibracin de Modelos de Comportamiento deHDM-III y HDM-4 para Pavimentos Asflticos a las Condiciones de Chile. Revista BIT N 25, March 2002.Santiago, Chile

de Solminihac H., Hidalgo P., Salgado M., Valdes M. (2002b) Calibracin del Modelo de Progresin de laRugosidad (IRI) para Pavimentos Asflticos en HDM-4 a las Condiciones de Chile. Revista Ingenieria deConstruccin - RIC Volumen 17 N2. May - August 2002. Santiago, Chile.

de Solminihac H., Hidalgo P., Salgado M., Bengoa E., Altamira A. (2003) Calibration of structural crackingmodels for asphalt pavements: The HDM-4 case. Indian Journal of Engineering and Materials SciencesJune, N 10, pag. 202-206. India, 2003.

Departamento de Gestin Vial (2002a). Evaluacin Tcnico Econmica de la Red Vial Nacional, June 2002,Ministry of Public Works, Chile.

Departamento de Gestin Vial, (2002b). Proposicin de Acciones de Mantenimiento y Estado de la Calzadapara Caminos Pavimentados de la Red Vial Nacional. March 2002, Ministry of Public Works, Chile.

Kerali H.G.R. (2000) Overview of HDM-4. The Highway Development and Management Series, VolumeFour, Association Mondiale de la Route AIPCR.

Schliesser, A. and Bull, A. (1992) Caminos: Un Nuevo Enfoque para la Gestin y Conservacin de RedesViales. Economic Commission for Latin-America and Caribbean (CEPAL), United Nations. Santiago, Chile,1992.

U.S. Department of Transportation (1999). Asset Management Primer, Federal Highway Administration,Office of Asset Management, December 1999.

Watanatada, T., Harral, C.G., Paterson, W., Dhareshwar, A.M., Bhandari, A., and Tsunokawa K. (1987) TheHighway Design and Maintenance Standards Model: Vol I. World Bank, Transportation Department,Washington D.C.

ACKNOWLEDGEMENTSAuthors wish to recognize the continuous technical and financial support given by the Ministry of PublicWorks of Chile during this study, and to the rest of the complete research team: Jaime Artigas, SergioRudolphy, Claudio Garn and E. Varas. The authors also wish to thank to Project MECESUP PUC 9903 forthe financial support given to this study.

BIOGRAPHY OF PRESENTING AUTHOR

Dr. Hernan E. de Solminihac

Since graduation as a civil engineer in 1981 from the Pontificia Universidad Catolica of Chile, Dr. de

Solminihac has been a faculty member in the School of Engineering of that university. He has been teachingseveral courses, leading many research projects in the Construction Engineering and ManagementDepartment, and acted as an expert consultant for the government and privates, especially in theinfrastructure management area.

Dr. de Solminihac has worked as Director of different projects on developing a pavement maintenancesystem for flexible pavements at his university, for the Ministry of Public Works of Chile. He was also theresearch director of the project that developed the concrete pavement management module included in theWorld Banks HDM-4 computational program. He is author of several papers and books. At the present time,professor de Solminihac is associate dean of administrative and research affaires in the School ofEngineering at the Catholic University of Chile.


TRB Committee AFD10 on Pavement Management Systems is providing the information contained herein for use by individual practitionersin state and local transportation agencies, researchers in academic institutions, and other members of the transportation research

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Evaluation of Maintenance Activities in Terms of Chile's Road Infrastructure Asset Value