Geospatial Pavement Distress Maintenance Management (Case Study from Entoto to Center of Chancho Town Road Section
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Date
2020-09
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Addis Ababa University
Abstract
GIS and GPS based pavement distress and maintenance management are
becoming a significant topic in the current pavement management industry and
research. There exists pavement distress from Entoto – the center of Chancho
town. GIS and GPS based analysis is important to manage the road section
distresses by ranking for maintenance according to priorities.
This study examines pavement distress and maintenance management systems
by using GIS and GPS tools or analysis and decision making. Also, the research
evaluates the relationship between pavement distresses, slope factor, drainage,
mobility, pavement performance, riding comfort, maintenance system, and
recommended treatments.
Initially, interviews were conducted to know about overall information. Then
conduct an observation and surveying to get the type, severity, and extent level of
distresses. Capturing images were also taken to look through the condition of
distresses, to get the geospatial coordinate points and their respective stations
using a GPS map camera. Finally examine factors for maintenance prioritization
(like AHP priority vector, PDI, and TBMC), use them as input data for weighted
overlay analysis, and prioritize distresses for maintenance using GIS software.
The preliminary results of the research show that among a total of 126 road
distresses, 33 were alligator cracks, 32 were potholes, 29 were patchings, 19 were
ravelings, 8 were edge breaks, 3 were ruttings, 1 shoving, and 1 longitudinal crack.
From the weighted overlay analysis result, distresses that lies in high detected
areas maintained first and that lies in low detected areas maintained last.
The conclusion bound to be drawn that pavement distress maintenance
management through a combined effect of maintenance priority factors using GIS
software gives a better maintenance priority map. The traditional pavement
distress maintenance management systems don’t consider it and use pavement
condition data to give priorities for maintenance on the highway networks.
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Keywords
GIS, GPS map camera, pavement distress maintenance management, pavement distress maintenance priorities