For Pradhan Mantri Gram Sadak Yojana (PMGSY) roads, pavement condition survey is essential to estimate Pavement Condition Index (PCI) rating value for the road sections as well as for further verification of the estimated value by an auditor. PCI rates the condition of the surface of a road network in terms of a numerical rating and it is used to (a) identify maintenance, rehabilitation and / or up-gradation needs, (b) monitor pavement condition, (c) develop road maintenance budgets, (d) evaluate pavement materials and designs. In current field practice, PCI is determined manually by arithmetic mean value of three different ratings for each km of PMGSY road sections. This is very subjective and time consuming.
In this paper, authors proposed a methodology for automated estimation of PCI for PMGSY roads using pavement videos. Using the proposed methodology, geotagged pavement videos of PMGSY roads are captured without any artificial lighting systems using a pavement view video system. Then, the collected raw videos are processed automatically using a robust video image processing algorithm for accurate estimation of PCI value using pavement distress information extracted out of the pavement videos. The test results indicate that the proposed methodology has a significant capability in estimating PCI value as well as its further verification in less time and effort. And the proposed methodology for automation in PCI rating can be readily applied in professional practice as a reliable and accurate approach.
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Type
Presentation / Webinar
Author
Namita Akoijam
Organization
BETQ Data Analytics Pvt. Ltd.
Published in
2017
Submitted by
IRF
Related theme(s)
General, Finances & Economics, Governance
Region
All Regions
Country
All Countries