Prioritization of pavement maintenance sections using objective based Analytic Hierarchy Process

Ahmed, Sarfaraz; Vedagiri, P.; Rao, K. V. Krishna

doi:10.1016/j.ijprt.2017.01.001

Cited by 58 publications

(23 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Ahmed et al [7] used AHP to determine the maintenance/repair priority based on distress level of the sidewalk pavement and carried out a comparison study with existing RCI (Road Condition Index) by using the AHP result. The correlation analysis of each result of AHP, RCI and priority indicated Sustainability 2019, 11, 7086 3 of 13 79% correlation for the case of the AHP and RCI result, and 85% correlation for the case of priority, thus showing a satisfactory result.…”

Section: Using Ahp In Pavement Managementmentioning

confidence: 99%

“…Applying Equation (7) below, the result of Table 5 was obtained. Li et al (2017) [7] defined RI, which was used to compute CR, as shown in Table 6 below. CR = CI RI (7) CR of this study was computed to be 0.00001 as shown in Table 5 below, and RI values used for the calculation of CR are shown in Table 6.…”

Section: Consistencymentioning

confidence: 99%

“…Li et al (2017) [7] defined RI, which was used to compute CR, as shown in Table 6 below. CR = CI RI (7) CR of this study was computed to be 0.00001 as shown in Table 5 below, and RI values used for the calculation of CR are shown in Table 6. The computed CR indicates very high consistency of the questionnaire data collected in this study and its high validity [7].…”

Section: Consistencymentioning

confidence: 99%

“…CR = CI RI (7) CR of this study was computed to be 0.00001 as shown in Table 5 below, and RI values used for the calculation of CR are shown in Table 6. The computed CR indicates very high consistency of the questionnaire data collected in this study and its high validity [7]. Table 7 below shows the final result of computing weight of each distress type.…”

Section: Consistencymentioning

confidence: 99%

See 3 more Smart Citations

Development of Sidewalk Block Pavement Condition Index (SBPCI) using Analytical Hierarchy Process

et al. 2019

View full text Add to dashboard Cite

This study aimed at developing SBPCI (Sidewalk Block Pavement Condition Index) with sidewalk pavement condition survey data of Seoul city in order to attain a quantitative evaluation method of sidewalk pavement condition. The distress patterns of sidewalk pavement were classified into four groups of Crack/Loss, Roughness, Aging, and Corner Break. AHP (Analytic Hierarchy Process) technique was employed on the basis of the raking process of 31 pavement managers in order to analyze the influence of the distress patterns on the sidewalk pavement condition. The AHP analysis result indicated the weight of pop out, roughness, surface abrasion, and corner break were 0.521, 0.244, 0.164, and 0.070, respectively, by distress type. A model equation was derived by using the sidewalk pavement condition data from 420 sections. The correlation analysis between the result of the model equation and distress type revealed that the correlation of corner break was low to be excluded from SBPCI model; while pop out, roughness, and surface abrasion were statistically significant to be used as three variables of the developed SBPCI model.

show abstract

Section: Using Ahp In Pavement Managementmentioning

confidence: 99%

Section: Consistencymentioning

confidence: 99%

Section: Consistencymentioning

confidence: 99%

Section: Consistencymentioning

confidence: 99%

See 2 more Smart Citations

Development of Sidewalk Block Pavement Condition Index (SBPCI) using Analytical Hierarchy Process

et al. 2019

View full text Add to dashboard Cite

show abstract

“…Many maintenance prioritization methods have been developed in many countries [4 -12]. Analytical hierarchy process (AHP) is the most commonly method used by researchers for determining pavement maintenance priority [4,6,7,9,10]. As a method, AHP is used in various fields of science.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of road maintenance priority using PCI and road note 1 for Indonesian district roads

Siswanto

Supriyanto

Pranoto

et al. 2018

AIP Conference Proceedings

View full text Add to dashboard Cite

Abstract. It is likely that resources for road maintenance will be limited, and the decisions will be required in the most effective way of applying them. This means the importance to determine the priority of road maintenance. The objective of this research was to evaluate the road maintenance priority using Pavement Condition Index (PCI) and Road Note 1 for Indonesian district roads. Locations for this research were the roads in Jombang and Blitar district and 8 (eight) road segments were taken from each district. Distress data was taken by visual observation referred to ASTM D6433. There were 20 distress types that had been recorded. Method of determining road maintenance priority was Road Note 1. The results of the research as obtained from the combination method of PCI and Road Note 1 for survey and prioritization, can be identified as follows: four road segments are in good condition, four are satisfactory, four are in fair condition, two are in poor condition, one is in a very poor condition, and one road segment is in serious condition. In total, 12 of 16 road segments are in stable condition. The use of the combination of PCI and Road Note 1 with modifications in Indonesian district roads merits consideration. The modification is required especially for traffic levels greater than 1000 vehicles/day to be split into more details to accommodate the Indonesian traffic.

show abstract

Arable land in Northwest China: Dynamics analysis of health and productivity in 2000–2020

Shuchen,

Yimin,

Pingda

et al. 2024

Land Degrad Dev

View full text Add to dashboard Cite

Arable land health (ALH) and arable land productivity (ALP) are crucial indicators of agricultural ecological functionality and sustainability. The shift of grain‐producing regions in Northwest China has led to arable land degradation, which endangers both food production and sustainable development. Several studies have focused on arable land quantity, distribution, and regional features, but ALH and sustainable ALP have received little attention. For the first time, we investigated the spatio‐temporal distribution and coupling connection between ALH and ALP in Northwest China (NC) using soil health indicators. Our study revealed the following key findings: (1) A minimal dataset of 12 indicators can efficiently replace the total dataset to evaluate the arable land health index in NC. (2) Over the last 20 years, the high and sub‐high grades of ALH increased by 536.8% and 222.6%, respectively, with a shift toward the northwest. During the specified period, ALH with low health and underutilized grade decreased by 46.01% and 69.4%, respectively, primarily in Xinjiang and Inner Mongolia. At the county level, ALP increased by 26%, primarily in northern Xinjiang and southern Gansu. 71% of counties remained stable, while only 3% experienced a decline. (4) The relationship between ALH and ALP were divided into six coupled groups that form an inverted “U” shape. High‐production areas were generally strongly linked, while low‐production areas were weakly coupled. Over the last 20 years, NC has seen significant improvements in ALH, coinciding with an increase in ALP. However, in most cases, the relationship between ALH and ALP were negative or weak.

show abstract

Prioritization of pavement maintenance sections using objective based Analytic Hierarchy Process

Cited by 58 publications

References 4 publications

Development of Sidewalk Block Pavement Condition Index (SBPCI) using Analytical Hierarchy Process

Development of Sidewalk Block Pavement Condition Index (SBPCI) using Analytical Hierarchy Process

Evaluation of road maintenance priority using PCI and road note 1 for Indonesian district roads

Arable land in Northwest China: Dynamics analysis of health and productivity in 2000–2020

Contact Info

Product

Resources

About