|
UWSpace >
University of Waterloo >
Electronic Theses and Dissertations (UW) >
Please use this identifier to cite or link to this item:
http://hdl.handle.net/10012/5799
|
| Title: | An Automatic Image Recognition System for Winter Road Condition Monitoring |
| Authors: | Omer, Raqib |
| Keywords: | Machine Vision
Winter Maintenance |
| Approved Date: | 22-Feb-2011 |
| Date Submitted: | 17-Feb-2011 |
| Abstract: | Municipalities and contractors in Canada and other parts of the world rely on road
surface condition information during and after a snow storm to optimize maintenance operations
and planning. With an ever increasing demand for safer and more sustainable road
network there is an ever increasing demand for more reliable, accurate and up-to-date road
surface condition information while working with the limited available resources. Such high
dependence on road condition information is driving more and more attention towards analyzing
the reliability of current technology as well as developing new and more innovative
methods for monitoring road surface condition. This research provides an overview of the
various road condition monitoring technologies in use today. A new machine vision based
mobile road surface condition monitoring system is proposed which has the potential to
produce high spatial and temporal coverage. The proposed approach uses multiple models
calibrated according to local pavement color and environmental conditions potentially
providing better accuracy compared to a single model for all conditions. Once fully developed,
this system could potentially provide intermediate data between the more reliable
xed monitoring stations, enabling the authorities with a wider coverage without a heavy
extra cost. The up to date information could be used to better plan maintenance strategies
and thus minimizing salt use and maintenance costs. |
| Program: | Civil Engineering |
| Department: | Civil and Environmental Engineering |
| Degree: | Master of Applied Science |
| URI: | http://hdl.handle.net/10012/5799 |
| Appears in Collections: | Faculty of Engineering Theses and Dissertations
Electronic Theses and Dissertations (UW)
|
This item is protected by original copyright
|
All items in UWSpace are protected by copyright, with all rights reserved.
|
