F1000ResearchF1000Research2046-1402F1000 Research LimitedLondon, UK10.12688/f1000research.171563.1Research ArticleArticlesValues Deduced to Apply the Pavement Condition Index Methodology to Ecuador
[version 1; peer review: 1 approved, 1 not approved]
BRITOJESSICAConceptualizationInvestigationMethodologyhttps://orcid.org/0000-0001-5550-5688a1AndradeAlexisConceptualizationInvestigationMethodology1EdisonVillacrésSupervisionValidation1MerinoCarolinaWriting – Original Draft Preparation1VallejoRobertoWriting – Review & Editing2
Engineering, National University of Chimborazo, Riobamba, Chimborazo Province, 060150, Ecuador
Territorial Planning, Goverment of Riobamba, Riobamba, Chimborazo, 060104, Ecuadorjessica.brito@unach.edu.ec
Road maintenance is essential for preserving the useful life of the roads. The evaluation methodology used in Ecuador is the Pavement Condition Index (PCI) method. It is the most complete method based on the analysis of the functional and structural damages that the pavement presents, the same ones that depend on its class, severity, and quantity. The PCI methodology uses data based on experiments made in the United States, so when evaluating pavements in Ecuador using the said methodology, it is not a correct adaptation to our reality because of the differences in deterioration of climatic factors and construction aspects. The PCI methodology has a study of values deduced from each of the damages present on the road, which are very strict in their qualification because the pavement service index in the United States looks for roads with high-quality standards compared to the Ecuadorian reality, where economic factors such as restrictions on usual road maintenance. The research proposes to generate changes in the abacus that generate the deduced values of the PCI methodology and adapt them to our country. Resulting in a 20% variability in the Ecuadorian Pavement Serviceability Index (PSI), which was applied to the Pavement Condition Index (PCI) method, commonly used for pavement evaluation.
PavementmethodconditionservicedamageThe author(s) declared that no grants were involved in supporting this work.1. Introduction
One of the most complete pavement evaluation methods used worldwide is the PCI (Pavement Condition Index), a method developed by
Shahin & Kohn (1979) originates in the technical report M - 268 published by the United States Army Corps of Engineers (1968). This methodology allows us to assess the condition of road pavement, taking into account the deterioration that the road may have at the time of evaluation. The purpose of using the methodology is to ensure proper maintenance based on the level of deterioration.
The type of maintenance chosen for a road must ensure that Fthe road meets its intended lifespan. Therefore, it is crucial to recognize that preventive maintenance may not reveal severe conditions of the road, potentially leading to increased costs to provide optimal road service, periodic conservation and maintenance actions, on the other hand, extend the road’s lifespan and keep it in acceptable operating conditions (
Obregón-Biosca et al., 2015).
Nowadays, due to the functional and structural characteristics provided in roadways, asphalt pavements are the most widely used in the construction of road networks in the majority of countries. The quality and design of the asphalt mixtures used in these pavements largely depend on their performance during the operational or service phase (
Zhao et al., 2025).
The PCI method utilizes values derived from charts by ASTM (American Society for Testing and Materials) Standard D6433 - 03, titled “Standard Practice for Roads and Parking Lots Pavement Condition Index Surveys.” The values prescribed in the standard are associated with factors contributing to pavement deterioration, which manifests from the moment a road is constructed (
Choez Pibaque, 2022). Various methodologies exist for pavement evaluation, including Visual Inspection of Road Infrastructure (VIZIR), PCI, and Pavement Surface Evaluation and Rating (PASER).
The choice of pavement evaluation method will depend on each country and its stakeholders, considering the specific needs of each region (
Vásquez Varela, 2002). For instance, in Ecuador, the PCI methodology is employed due to its ease of calculation and the fact that it does not necessitate specific tools or equipment for its application. However, this methodology bases its results on studies conducted in a country with a different context than the local one, rendering these results less suitable for accurate evaluation.
Several models and methodologies are integral components of management systems, originating from the detailed analysis of the current state of roadways. The objective is to bring about a change in the interurban-urban landscape through the prediction of deterioration (
Guaita Luján, 2016).
In Nevada and Louisiana, United States, an analysis of the road conditions has been conducted using a methodology tailored to the specific characteristics of the region. This has allowed the execution of practical and accurate studies to evaluate the roadways, employing computerized applications
ASTM International (2003). However, it has been identified that these analyses in Nevada and Louisiana do not lead to changes or variations in the deduction curves inherent to the method (
Loria et al., 2016). Similarly, in Iran and India, there has been an exploration of the possibility of using programs that automate calculations, such as Soft Computing and Information Solutions. These programs assess pavement conditions using historical data to predict the value of the Pavement Condition Index (PCI). Although these software applications contribute to research, they do not exhibit similar characteristics (
Shahnazari et al., 2012).
In South America, research on pavement conditions has been conducted in Chile, Venezuela, Peru, and Colombia. These studies are primarily based on the PCI method, and through manuals and software applications, they have facilitated the calculation of PCI. It is important to cite several investigations that have contributed to our research, such as the work of the
Saba et al., (2006),
Rodriguez Velasquez (2009),
Nuñez Caiminagua & Salazar Avilés (2015),
Hurtado Arias (2016) and
Ibragimov et al., (2024).
These researchers have conducted roadway studies using the PCI method without alterations, employing it solely to generate road maintenance plans. This research aims to establish values for determining the local pavement condition index based on the conditions and characteristics of Ecuadorian roadways, using the local Pavement Serviceability Index (PSI).
2. Methodology
The deduction curves used by the PCI methodology are based on the Service Index Pavements, these two values being significantly related, so the curves will be the result of the factors that affect the Service Index Pavements (
Vásquez Varela, 2002). The deduction curves determined in this research will be evaluated by experts as part of the Validation process of the research results.
The evaluation will also consider the Pavement Serviceability Index (PSI), related to climatic, geographical, and environmental factors associated with each roadway. The resulting PSI values will be analyzed using statistical methods, supported by graphs and tables. The simplicity of obtaining PSI makes it an easily accessible value, as it does not require a specific prior study to determine.
To get the Pavement Serviceability Index, it suffices to have a well-maintained vehicle. The individual responsible for obtaining this value will remain inside the vehicle, focusing on perceiving and determining the PSI value. Additionally, the person inside the vehicle should assess the roadway based on the movement experienced while traveling. This approach serves as an effective means for users to determine the extent of damage, such as potholes or irregularities, allowing for the evaluation of whether the roadway is in good condition, facilitating reliable service, or if it is in poor condition.
Upon analyzing all the data, new curves of deduced PCI values tailored to the Ecuadorian context will be generated. Through this methodology, maintenance plans will be formulated to align with our local reality, recognizing that the continuous assessment and upkeep of roads contribute to the proper formation of the road network, a necessity for both the social and economic development of Ecuador.
An adequate road maintenance process seeks greater accuracy as much as possible since it would generate a lower government cost for roads currently the data obtained by the Ministry of Transportation and Public Works presents a value of 200 million dollars annually specifically for road maintenance using the PCI methodology.
According to the characteristics of our areas and with values based on our road reality, the methodology will show us more real and accurate results. In Ecuador, for every road maintenance plan, studies are needed through methods such as Vizir (French auscultation methodology) and PCI. In Ecuador, through the Ministry of Transportation and Public Works, the evaluation of the condition of existing pavements in the territory has been carried out using the PCI Method, however, only the values of the method have been considered. It is necessary to investigate roads in the countries, as it is an important point for their emergence.
3. Results3.1 Study area
This study was conducted on the roads of the province of Chimborazo, using field data collected based on pavement failures. The data on pavement failures is crucial for ensuring the accuracy of the results obtained during processing, facilitating the development of maintenance and rehabilitation strategies for the roads. The Pavement Condition Index (PCI) values, by the ASTM D6433-03, will be determined for each route and compared with the Pavement Serviceability Index (PSI) obtained through the AASHTO-93 standard (
American Association of State Highway and Transportation Officials - Design of pavement structures; AASHTO, 1993). The scope of the study is limited to roads that are part of the Ecuadorian national network, specifically those related to Chimborazo.
3.2 Deduction curves based on the analysis of PCI vs PSI of road sections
To get the percentage that the PCI in Ecuador is below the PCI in the United States, 15 samples of road sections in the province of Chimborazo were analyzed, to appreciate the variability that the Pavement Condition Index will have, this is obtained through the abacuses proposed by the original PCI methodology regarding the local Service Index.
The roads in the United States undergo continuous maintenance, considering high-quality standards to be optimal, therefore, the penalty imposed by these abacuses is quite high, generating a low PCI compared to our local reality. Active 1: The deterioration factors that directly influence the generation of new deterioration curves will penalize the deduced values, thus obtaining a PCI for Ecuador that should be higher compared to the original methodology.
To carry out the analysis of the Deduction curves, we started by looking for the best road sections, those that provide a “Very Good” PSI Ecuador index according to our assessment, and from 15 samples taken, the Pavement Service Index was determined, which is compared with the optimal PSI according to the ASSHTO, resulting in variability of 20% as shown in
Table 1 and
Figure 1 because in our country the roads still provide ideal service conditions and according to the penalty of foreign regulations they are not found in such a way.
Sampling values and percentage of variation.
Road section
PSI optimal
PSI ecuador optimal
1
5.00
4.1
2
5.00
3.8
3
5.00
4.2
4
5.00
4.2
5
5.00
4.0
6
5.00
3.9
7
5.00
4.0
8
5.00
4.2
9
5.00
3.8
10
5.00
3.8
11
5.00
3.9
12
5.00
3.8
13
5.00
4.1
14
5.00
4.1
15
5.00
4.1
Average
5.00
4.0
Road State
Good
Good
%
100%
80%
Variation Of Percentage
20%
PSI (EEUU-Optimal) Vs. PSI (Ecuador).
A. Road pavement condition index focused on ecuador, based on evaluation of pavement serviceability index
The 20% variability in the Ecuadorian Pavement Serviceability Index (PSI) was considered and applied to the Pavement Condition Index (PCI) method, commonly used for pavement evaluation. This choice was made because the values derived from the PCI method are the ones that penalize pavement conditions. This variability can be differentiated in
Table 2 and
Table 3.
PSI ASSHTOO and PCI.
PSI (AASHTO)
Condition
PCI
5
4
Good
100%
80%
4
3
Satisfactory
80%
60%
3
2
Fair
60%
40%
2
1
Poor
40%
20%
1
0
Very Poor
20%
0%
PSI Ecuador and PCI Ecuador.
PSI (AASHTO)
Condition
PCI
5
4
Good
100%
80%
4
3
Satisfactory
100%
80%
3
2
Fair
80%
60%
2
1
Poor
60%
40%
1
0
Very Poor
40%
20%
With the analysis performed previously and adapting the variations to the local reality, we obtain the deduction curves for each damage (
Figures 2–
6) and the general curve to determine the corrected deduction value (
Figure 7). In this context, 19 deduction curves are proposed for each type of failure in the flexible pavement such as: Alligator Cracking, Bleeding, Block Cracking, Bumps and Sags, Corrugation, Depression, Edge Cracking, Joint Reflection Cracking, Lane/Shoulder Drop Off, Longitudinal & Transversal Cracking, Patching & Utility Patching, Polished Aggregates, Potholes, Railroad Crossing, Rutting, Shoving, Slippage Cracking, Swell, Weathering/Raveling. It should be noted that each type of failure has a high (H), medium (M) and low (L) severity level. The curves described above have been adapted from the failure types developed by the United States Army Corps of Engineers (USACE) and are documented in the American standard ASTM D6433.
Alligator cracking, bleeding, block cracking, bumps and sags.
The variation of the Pavement Condition Index (PCI) by 20% from the AASHTO, based on the service required by our road reality, allowed the determination of each point where the curves of original deduced values from the PCI methodology are defined. Polynomial equations governing each logarithmic curve could be generated, considering an 80% penalty relative to the 100% recommended by the standard for each of the 19 damages. Damage number 19, related to weathering, could be considered as aggregate polished aggregates, penalizing with values lower than the deduced ones. However, it exhibits similar deterioration characteristics, leading to the definition of the same deduction curves.
Future research should aim to establish a database using the results obtained in this study and compare them with data obtained previously with no variation in the methodology. This comparison would help identify whether an appropriate budget for maintenance plans in Ecuador can be achieved based on these results.
Ethical approval
This research did not involve human participants, human data, or biological samples. Therefore, ethical approval from an institutional review board (IRB) or ethics committee was not required. The study focused exclusively on engineering analysis and the evaluation of pavement condition data obtained from secondary, non-human sources.
Data availability
Repository:
Zenodo —
Dataset associated with the article “Values Deduced to Apply the Pavement Condition Index Methodology to Ecuador”
https://doi.org/10.5281/zenodo.17342626
This project contains the following underlying data:
DATA_DEDUCED_VALUES.xlsx (data supporting the deduction values obtained for Ecuador). (
Jéssica, B., Alexis, A., Edison, V., Carolina, M., & Roberto, V. (2025).)
Data are available under the terms of the
Creative Commons Attribution 4.0 International License (CC BY 4.0).
ReferencesAmerican Association of State Highway and Transportation Officials:
AASHTO guide for design of pavement structures.AASHTO;1993.ASTM International:
Standard practice for roads and parking lots pavement condition index surveys (ASTM D6433-03).ASTM International;2003.
10.1520/D6433-03Choez PibaqueVI:
Determination of the pavement condition index of Macará street in the Jipijapa canton using the methodology PCI.2022. [bachelorThesis,Jipijapa-Unesum].
Reference SourceGuaita LujánB:
Urban pavement maintenance management. proposal for the implementation of a pavement management system in the city of Valencia. Quantification of the benefits of implementing a pavement management system.Valencia, Spain:
Polytechnic University of Valencia;2016.
Reference SourceHurtado AriasWM:
Functional and structural evaluation to determine the deterioration of the pavement structure on Abdón Calderón Avenue, Conocoto parish, Quito canton, Pichincha province.2016. [bachelorThesis, Quito/UIDE/2016].
Reference SourceIbragimovEKimYLeeJH:
Automated Pavement Condition Index Assessment with Deep Learning and Image Analysis: An End-to-End Approach.Sensors.2024;24(7):Article 7.
3861054510.3390/s24072333PMC11014408JéssicaBAlexisAEdisonV:
Dataset associated with the article “Values Deduced to Apply the Pavement Condition Index Methodology to Ecuador”.[Data set].
Zenodo.2025.
10.5281/zenodo.17342626LoriaLHajjENavasA:
Review and Improvement of Pavement Condition Prediction Models for Flexible Pavements Using Statistical Techniques (Bachelor’s Thesis).Pitra, Costa Rica:
University of Costa Rica;2016.
Reference SourceNuñezJSalazarN:
Manual for the Acquisition of the Undergraduate Degree Title ‘Conservation and Maintenance Processes in Flexible Pavements for the Province of Chimborazo’.Chimborazo, Ecuador:
National University of Chimborazo;2015. (Bachelor’s Thesis).
Reference SourceObregón-BioscaSARomero-NavarreteJABetanzo-QuezadaE:
Mobility in a Mexican metropolitan area, case study: Querétaro, Mexico.Transport and Territory Magazine.2015;12:167–197.
Reference SourceRodriguezED:
Calculation of the Flexible Pavement Condition Index on Luis Montero Avenue, Castilla District.Piura, Peru:
University of Piura;2009. (Bachelor’s Thesis).
Reference SourceSabaRGHuvstigAHildebrandG:
Performance Prediction Models for Flexible Pavements: A State-of-the-art Report.2006;54.
Reference SourceShahnazariHTutunchianMAMashayekhiM:
Application of Soft Computing for Prediction of Pavement Condition Index.J. Transp. Eng.2012;138:1495–1506.
10.1061/(ASCE)TE.1943-5436.0000454ShahinMYKohnSD:
Development of a pavement condition rating procedure for roads, streets, and parking lots.1979;2.
Reference SourceVásquez VarelaLR:
Pavement Condition Index (PCI) for asphalt and concrete pavements on roads.Ingepav.2002;1:2–45.
Reference SourceZhaoQYaoXDengA:
Fatigue Performance of New and Recycled Asphalt Pavement with Interlayer Based on Ct Test (SSRN Scholarly Paper 5143812).Soc. Sci. Res. Netw.2025.
10.2139/ssrn.514381210.5256/f1000research.189184.r435139Reviewer response for version 1LabiSamuel1Referee
Purdue University, West Lafayette, Indiana, USA
Competing interests: No competing interests were disclosed.
This is a short and simple study, yet serves as a valuable contribution in the specific context of pavement management in Equador. The article is ready for publication, in my opinion, after it has been proofread by a technical wrtiter and editor to paraphrase some of the sentences and correct the typos.
Is the work clearly and accurately presented and does it cite the current literature?
Yes
If applicable, is the statistical analysis and its interpretation appropriate?
Yes
Are all the source data underlying the results available to ensure full reproducibility?
Yes
Is the study design appropriate and is the work technically sound?
Yes
Are the conclusions drawn adequately supported by the results?
Yes
Are sufficient details of methods and analysis provided to allow replication by others?
Yes
Reviewer Expertise:
Infrastructure management
I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.
10.5256/f1000research.189184.r436765Reviewer response for version 1IldefonsoJesner Sereni1Refereehttps://orcid.org/0000-0003-2799-8600
Universidade Estadual de Maringá, Maringá, Brazil
Competing interests: No competing interests were disclosed.
This article proposes an adaptation of the Pavement Condition Index (PCI) methodology for application in Ecuador by modifying the deduction curves based on an observed 20% variability in the Pavement Serviceability Index (PSI) relative to the reference values traditionally associated with AASHTO and ASTM standards. Using 15 road sections in Chimborazo Province, the authors infer a local serviceability adjustment and apply this factor uniformly to the PCI abacuses, generating new deduction curves for 19 flexible pavement distress types. The objective is to better align pavement condition assessment and maintenance planning with Ecuadorian climatic, economic, and operational realities.
The topic is relevant and potentially valuable for pavement management in developing contexts. However, in its current form, the manuscript presents fundamental methodological and conceptual weaknesses that prevent the results from being considered technically sound or reproducible.
Major comments
1. Definition and measurement of PSI
A critical issue concerns how the Pavement Serviceability Index is defined and obtained. The manuscript states that PSI is determined by a person inside a well-maintained vehicle, based on perceived motion and ride quality. This description does not correspond to the AASHTO PSI formulation and is much closer to a subjective ride rating or Present Serviceability Rating (PSR).
Because the entire calibration strategy and the proposed 20% adjustment are based on this value, the lack of a clear and standard-consistent definition undermines the validity of the results.
Required actions
Clearly define whether the study uses PSI, PSR, or another subjective serviceability indicator.
Provide a complete measurement protocol, including number of raters, training, vehicle characteristics, speed, repetition, and environmental conditions.
Quantify reliability, at minimum inter-rater and test–retest agreement.
2. Justification and generalization of the 20% adjustment factor
The 20% variability is derived from a limited sample of 15 road sections and then applied uniformly to all deduction curves, for all distress types and severity levels. No statistical justification or mechanistic explanation is provided to support the assumption that a single scaling factor is valid across fundamentally different distress mechanisms.
Different distresses influence serviceability and user perception in distinct ways, and a global adjustment factor is a strong assumption that must be demonstrated, not asserted.
Required actions
Provide a transparent derivation of the 20% value, including dispersion measures and uncertainty.
Assess whether the adjustment varies by distress type, severity, or density.
Perform sensitivity or validation analyses using independent performance indicators or maintenance outcomes.
3. Insufficient methodological detail for replication
The description of the PCI survey and curve adaptation process lacks essential details required for replication.
Missing or unclear elements include:
Criteria for road section selection and representativeness;
Definition of sample units and survey units;
Distress identification, quantification, and severity classification procedures;
Numerical process used to modify the original deduction curves;
Curve fitting procedures, including fitting method, data points, and goodness-of-fit metrics.
Required actions
Add a step-by-step, reproducible workflow describing the entire process from field survey to final PCI calculation.
Provide numerical tables or equations defining each adapted deduction curve and their valid ranges.
Include a worked example demonstrating the full PCI calculation using the proposed method.
4. Absence of formal statistical analysis
Although the manuscript states that PSI values are analyzed statistically, the presented results are descriptive only. No statistical tests, uncertainty analysis, or reliability assessment is reported. Given the subjective component of the serviceability evaluation, this omission is significant.
Required actions
Include appropriate statistical analyses, such as reliability metrics for subjective ratings and uncertainty bounds for derived adjustments.
Report calibration or fitting metrics if polynomial or logarithmic curves are generated.
Justify sample size and analytical choices.
5. Data availability and reproducibility
The availability of a Zenodo dataset is a positive aspect. However, the current description does not ensure full reproducibility.
For complete transparency, the repository should include:
Raw field survey data for PCI and serviceability evaluations;
Intermediate calculation steps linking raw data to adapted curves;
Scripts or fully documented spreadsheets used in curve generation.
Required actions
Expand the data repository to include raw observations and transformation steps.
Provide documentation sufficient for an independent researcher to reproduce the results.
Minor comments
The literature review could be strengthened by discussing prior attempts to localize or calibrate PCI systems internationally and clearly positioning the novelty of this work.
Several contextual statements regarding national practice and maintenance costs require stronger referencing.
Terminology should be clarified and standardized throughout the manuscript.
Figures presenting adapted curves should include explicit comparison with original ASTM curves, with quantitative differences highlighted.
Overall recommendation
In its current form, the manuscript does not meet the technical and methodological standards required for a calibration or adaptation study of the PCI methodology. The study has potential relevance, but major revisions are necessary. The authors must clarify the serviceability metric, justify the calibration strategy, provide full methodological transparency, and validate the proposed curves before the work can be considered scientifically sound.
Is the work clearly and accurately presented and does it cite the current literature?
Partly
If applicable, is the statistical analysis and its interpretation appropriate?
No
Are all the source data underlying the results available to ensure full reproducibility?
Partly
Is the study design appropriate and is the work technically sound?
No
Are the conclusions drawn adequately supported by the results?
Partly
Are sufficient details of methods and analysis provided to allow replication by others?
I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above.