Integration of GIS and Data Mining Technology to Enhance the Pavement Management Decision Making
Publication: Journal of Transportation Engineering
Volume 136, Issue 4
Abstract
This paper presents a research effort undertaken to explore the applicability of data mining and knowledge discovery (DMKD) in combination with Geographic Information System (GIS) technology to pavement management to better decide maintenance strategies, set rehabilitation priorities, and make investment decisions. The main objective of the research is to utilize data mining techniques to find pertinent information hidden within the pavement database. Mining algorithm C5.0, including decision trees and association rules, has been used in this analysis. The selected rules have been used to predict the maintenance and rehabilitation strategy of road segments. A pavement database covering four counties within the state of North Carolina, which was provided by North Carolina DOT (NCDOT), has been used to test this method. A comparison was conducted in this paper for the decisions related to a rehabilitation strategy proposed by the NCDOT to the proposed methodology presented in this paper. From the experimental results, it was found that the rehabilitation strategy derived by this paper is different from that proposed by the NCDOT. After combining with the AIRA Data Mining method, seven final rules are defined. Using these final rules, the maps of several pavement rehabilitation strategies are created. When their numbers and locations are compared with ones made by engineers at the Institute for Transportation Research and Education (ITRE) at North Carolina State University, it has been found that error for the number and the location are various for the different rehabilitation strategies. With the pilot experiment in the project, it can be concluded: (1) use of the DMKD method for the decision of road maintenance and rehabilitation can greatly increase the speed of decision making, thus largely saving time and money, and shortening the project period; (2) the DMKD technology can make consistent decisions about road maintenance and rehabilitation if the road conditions are similar, i.e., interference from human factors is less significant; (3) integration of the DMKD and GIS technologies provides a pavement management system with the capabilities to graphically display treatment decisions against distresses; and (4) the decisions related to pavement rehabilitation made by the DMKD technology is not completely consistent with that made by ITRE, thereby, the postprocessing for verification and refinement is necessary.
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Acknowledgments
The pavement database was provided by Greg Ferrara, GIS Program Manager at the Institute for Transportation Research and Education (ITRE) of North Carolina State University. John Roklevi at the ITRE provided essential help in data delivery, data interpretation, and explanation related the metadata. The writers sincerely thank both of them. The writers also thank the project administrators for granting permission to use their data.
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Information & Authors
Information
Published In
Journal of Transportation Engineering
Volume 136 • Issue 4 • April 2010
Pages: 332 - 341
Copyright
© 2010 ASCE.
History
Received: Jul 25, 2008
Accepted: Jul 31, 2009
Published online: Aug 3, 2009
Published in print: Apr 2010
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