Development of Overall Pavement Condition Index for Urban Road Network

Shah, Yogesh U.; Jain, Shailendra Pratap; Tiwari, Diwakar; Jain, Manoj

doi:10.1016/j.sbspro.2013.11.126

Cited by 115 publications

(42 citation statements)

References 4 publications

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“…In India [32,33], and in other developing countries [34,35], some researchers have developed methods combining different distress index equations and PCI using a reduced number of distresses starting with the ASTM D6433 catalogue. To each distress, different weights were assigned based on expert opinion to take into account their influence on overall pavement conditions.…”

Section: Introductionmentioning

confidence: 99%

A Specified Procedure for Distress Identification and Assessment for Urban Road Surfaces Based on PCI

Loprencipe

Pantuso

2017

Coatings

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Abstract:In this paper, a simplified procedure for the assessment of pavement structural integrity and the level of service for urban road surfaces is presented. A sample of 109 Asphalt Concrete (AC) urban pavements of an Italian road network was considered to validate the methodology. As part of this research, the most recurrent defects, those never encountered and those not defined with respect to the list collected in the ASTM D6433 have been determined by statistical analysis. The goal of this research is the improvement of the ASTM D6433 Distress Identification Catalogue to be adapted to urban road surfaces. The presented methodology includes the implementation of a Visual Basic for Application (VBA) language-based program for the computerization of Pavement Condition Index (PCI) calculation with interpolation by the parametric cubic spline of all of the density/deduct value curves of ASTM D6433 distress types. Also, two new distress definitions (for manholes and for tree roots) and new density/deduct curve values were proposed to achieve a new distress identification manual for urban road pavements. To validate the presented methodology, for the 109 urban pavements considered, the PCI was calculated using the new distress catalogue and using the ASTM D6433 implemented on PAVER TM . The results of the linear regression between them and their statistical parameters are presented in this paper. The comparison of the results shows that the proposed method is suitable for the identification and assessment of observed distress in urban pavement surfaces at the PCI-based scale.

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Section: Introductionmentioning

confidence: 99%

A Specified Procedure for Distress Identification and Assessment for Urban Road Surfaces Based on PCI

Loprencipe

Pantuso

2017

Coatings

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“…Comparisons were made between PCI values calculated using standard PCI procedures (19 distress types) and PCI values calculated using modified distress identification procedures developed by the Metropolitan Transportation Commission (seven distress types) [10] The study area in Ref. [11] consists of 10 urban road sections constituting 29.92 km of Noida city. The methodology includes identification of urban road sections, pavement distress data collection, development of individual distress index and finally developing a combined OPCI (Overall Pavement Condition Index) for the network.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The proposed index is expected to be a good indicative of pavement condition and performance. The developed OPCI was used to select the maintenance strategy for the pavement section [11].…”

Section: Literature Reviewmentioning

confidence: 99%

Effect of Sample Unit Size on Visually Examining Pavement Condition for Asphalt-Surfaced Roads

Devkota¹

2017

JCEA

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Road surface condition evaluation involves the collection of data over pavement surface for different types of distresses. The exercise consumes a lot of resources if the whole road section length is surveyed and may be prone to errors as a result of surveyors' fatigue. It is therefore important to develop a representative sample to be used when evaluating road condition manually. This study aimed at determining an adequate sample size for section level as well as a way forward for network level condition evaluation of highways in Nepal. Again the study was conducted to quantify the effects of altering the sample unit size for performing a distress survey according to the PCI (pavement condition index) and SDI (surface distress index) method separately for asphalt surfaced roads. The effect of reducing/increasing sample unit size was investigated adopting visual examination through field survey by eight teams in July, 2015, along the section of Banepa-Bardibas highway. The PCI was then calculated for each sample unit using standard deduct curves and PCI calculation methodology as per SHRP (Strategic Highway Research Program) recommendations and the computation of SDI was done as per DoR (Department of Roads) guidelines. The results show that 13% sample unit are needed for SDI and 21% for PCI computation, however, the results are out of the significant level. This is higher than DoR and SHRP guidelines. Again no strong relationship is observed between SDI and PCI values.

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“…The index was used to analyse the data bases generated from pavement condition survey. (Shah et al, 2013) developed an overall condition index for urban road network. Pavement Condition Index, Pavement Roughness Index, Pavement Structural Capacity Index and Pavement Skid resistance index were developed individually and all these were combined to develop an overall index.…”

Section: Introductionmentioning

confidence: 99%

Development of Probabilistic Deterioration Models and Prioritisation of Low Volume Roads for Maintenance

2017

IJTTE

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India is having the second largest road network in the world and low volume roads contributes to about 61% of the total road network. Low volume roads in the rural areas face serious problems due to absence of timely maintenance resulting from stringent budget availability. For proper management of these roads, scientific pavement management tools are necessary. Right maintenance treatment is to be given to the right place at the right time. For this, the roads in a network are to be prioritized based on its importance with regard to the extent of deterioration. The deterioration of the pavement can be both functional and structural. Hence, the functional distresses, roughness and deflection of the pavement were selected as the performance indicators in this study while prioritising. The collection of distress data over the pavement life is a tedious process, where as the collection of roughness data which is a result of the distresses occurring on pavement is much easier. This paper attempts to compare the unified pavement condition indices developed using two approaches i) using combination of distresses and characteristic deflection and ii) using a combination of roughness and characteristic deflection. For the purpose of prioritisation of roads, pavement deterioration prediction models that can predict the condition of pavements at a future time are essential. Probabilistic approach is considered while developing the pavement prediction models and critical percentile values were used for prioritisation purpose. For roughness and deflection, non linear deterministic models were first developed and the corresponding probabilistic models were arrived at. Unified pavement condition indices were developed using Analytic Hierarchy Process (AHP) and the priority of the roads was compared. AHP is a simple and effective tool which uses pair wise comparison and relies on the judgments of experts to derive priority scales. Comparative approach in AHP is intuitively appealing and supported by evidence from cognitive psychology. The result shows that the indices developed using both approaches are comparable and hence prioritisation of the low volume roads can easily be done using the index developed by combining roughness and deflection values.

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Development of Overall Pavement Condition Index for Urban Road Network

Cited by 115 publications

References 4 publications

A Specified Procedure for Distress Identification and Assessment for Urban Road Surfaces Based on PCI

A Specified Procedure for Distress Identification and Assessment for Urban Road Surfaces Based on PCI

Effect of Sample Unit Size on Visually Examining Pavement Condition for Asphalt-Surfaced Roads

Development of Probabilistic Deterioration Models and Prioritisation of Low Volume Roads for Maintenance

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