A Review of the Philippine Visual Condition Index by Experts' Validation
Abstrak
—The pavement performance indices were developed to address the challenge of quantifying the condition or performance of existing road networks. They are crucial to national resource programming and prioritization in asset preservation. Pavement Condition Index (PCI) is one of these metrics measured by observing the surface road defects of a road network. This index is referred to as the Visual Condition Index (VCI) in the Philippines and is being conducted by the Department of Public Works and Highways (DPWH). It was adopted from New South Wales, Australia, and was localized to indicate the surface condition of the national roads. Currently, the documented process of localizing the index cannot be traced. This study aims to scientifically evaluate the suitability of the localized version of VCI to the Philippines by developing and comparing it to a new rating condition based on the insights and proficiency of the local road practitioners and specialists representing all the District Engineering Offices (DEOs) of the DPWH in the Philippines. This new rating condition was developed by conducting an online survey that simulated road networks selected from historical data. On-site images of the selected roads were captured and used in the online survey evaluated by the practitioners and specialists. Correlation of the results using multiple regression and Artificial Neural Network (ANN) analyses were employed to formulate a new PCI. The comparison between the new asphalt and concrete pavement PCI models and the current VCI employed yield coefficient of determination values of 0.78 and 0.75, respectively. These findings suggest that the formulated PCI effectively reflects the VCI and confirms that it is tailored to the local condition.
Penulis (8)
Lea B. Bronuela-Ambrocio
Jamie Alea
B. Ramos
H. Palmiano
J. Paul
T. Dacanay
Lestelle V. Torio-Kaimo
Krezia Tactac
Akses Cepat
PDF tidak tersedia langsung
Cek di sumber asli →- Tahun Terbit
- 2024
- Bahasa
- en
- Sumber Database
- Semantic Scholar
- DOI
- 10.18178/ijscer.13.4.114-120
- Akses
- Open Access ✓