A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Comparison of Decision Makers’ Perspectives and Data-Driven Factors Affecting Pavement Condition in Khyber Pakhtunkhwa, Pakistan
Best practices dictate that road maintenance plans be drawn up based on the pavement conditions determined by routine inspection. However, in many cases, the maintenance strategy is based on the experience of decision-makers, rather than the actual conditions. In Khyber Pakhtunkhwa Province, Pakistan, there are more than 3,000 km of provincial roads, but the road condition does not match the desired level due to the absence of an effective maintenance strategy. This paper aims to compare the pavement deterioration factors in the four divisions of highways as evaluated by decision makers with the factors exhibited by the actual inspection data to determine whether they follow a similar or different pattern. For this purpose, the factors that affect the pavement condition from the decision makers’ perspective were extracted from a questionnaire survey of division-level road managers by cross-tabulation analysis and were then compared with factors identified by ordinal logistic regression analysis of the pavement condition data obtained from the department. The study revealed that some factors that affected pavement condition like traffic loading that were common to both the decision makers’ perspectives and inspection data collected from the department in all divisions. However, there were some differences like drainage condition having a more significant effect on pavement condition in some divisions more than others, which suggested that it is important to analyze routine inspection data to give a more thorough and holistic approach to maintenance planning.
Comparison of Decision Makers’ Perspectives and Data-Driven Factors Affecting Pavement Condition in Khyber Pakhtunkhwa, Pakistan
Best practices dictate that road maintenance plans be drawn up based on the pavement conditions determined by routine inspection. However, in many cases, the maintenance strategy is based on the experience of decision-makers, rather than the actual conditions. In Khyber Pakhtunkhwa Province, Pakistan, there are more than 3,000 km of provincial roads, but the road condition does not match the desired level due to the absence of an effective maintenance strategy. This paper aims to compare the pavement deterioration factors in the four divisions of highways as evaluated by decision makers with the factors exhibited by the actual inspection data to determine whether they follow a similar or different pattern. For this purpose, the factors that affect the pavement condition from the decision makers’ perspective were extracted from a questionnaire survey of division-level road managers by cross-tabulation analysis and were then compared with factors identified by ordinal logistic regression analysis of the pavement condition data obtained from the department. The study revealed that some factors that affected pavement condition like traffic loading that were common to both the decision makers’ perspectives and inspection data collected from the department in all divisions. However, there were some differences like drainage condition having a more significant effect on pavement condition in some divisions more than others, which suggested that it is important to analyze routine inspection data to give a more thorough and holistic approach to maintenance planning.
Comparison of Decision Makers’ Perspectives and Data-Driven Factors Affecting Pavement Condition in Khyber Pakhtunkhwa, Pakistan
RILEM Bookseries
Banthia, Nemkumar (editor) / Soleimani-Dashtaki, Salman (editor) / Mindess, Sidney (editor) / Dartey, Selorm (author) / Amir, Azam (author) / Henry, Michael (author)
Interdisciplinary Symposium on Smart & Sustainable Infrastructures ; 2023 ; Vancouver, BC, Canada
Smart & Sustainable Infrastructure: Building a Greener Tomorrow ; Chapter: 94 ; 1064-1075
RILEM Bookseries ; 48
2024-02-20
12 pages
Article/Chapter (Book)
Electronic Resource
English
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