A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Data Grouping Analysis of Asphalt Pavement Distress Using Sequential Cluster Method
Pavement condition index (PCI) is a comprehensive indicator describing the overall damage of pavement surface and can be used to determine the pavement maintenance needs. However, due to its combination of multiple distress, the same PCI score may represent different combinations of pavement distress, making it impossible to make accurate preservation decisions. Therefore, it is necessary to conduct a more detailed grouping study on pavement distress data and establish a relationship between the refined data packets and PCI. Based on the actual distress data of Shanghai urban asphalt pavement, this study firstly uses the sequential clustering method to group the pavement segment data according to the PCI score. Then the distress characteristics of each group were analyzed and the differences between different damages were quantitatively calculated. The results show that the impact of the pavement distress combination on PCI is not uniform and the PCI score cannot fully reflect the complexity of pavement distress. When the PCI level is moderate, the variability of the pavement distress combination is the largest.
Data Grouping Analysis of Asphalt Pavement Distress Using Sequential Cluster Method
Pavement condition index (PCI) is a comprehensive indicator describing the overall damage of pavement surface and can be used to determine the pavement maintenance needs. However, due to its combination of multiple distress, the same PCI score may represent different combinations of pavement distress, making it impossible to make accurate preservation decisions. Therefore, it is necessary to conduct a more detailed grouping study on pavement distress data and establish a relationship between the refined data packets and PCI. Based on the actual distress data of Shanghai urban asphalt pavement, this study firstly uses the sequential clustering method to group the pavement segment data according to the PCI score. Then the distress characteristics of each group were analyzed and the differences between different damages were quantitatively calculated. The results show that the impact of the pavement distress combination on PCI is not uniform and the PCI score cannot fully reflect the complexity of pavement distress. When the PCI level is moderate, the variability of the pavement distress combination is the largest.
Data Grouping Analysis of Asphalt Pavement Distress Using Sequential Cluster Method
Li, Li (author) / Guan, Ting-Ting (author) / Yang, Kun (author) / Xu, Zhou-Cong (author)
20th COTA International Conference of Transportation Professionals ; 2020 ; Xi’an, China (Conference Cancelled)
CICTP 2020 ; 1666-1678
2020-12-09
Conference paper
Electronic Resource
English
Automated Pothole Distress Assessment Using Asphalt Pavement Video Data
| British Library Online Contents | 2013
Automated Pothole Distress Assessment Using Asphalt Pavement Video Data
| Online Contents | 2013
EVALUATION AND MAINTENANCE OF ASPHALT PAVEMENT DISTRESS
| British Library Conference Proceedings | 2004