Title: A data analytics case study assessing factors affecting pavement deflection values

Authors: Majid Seyfi; Rakesh Rawat; Justin Weligamage; Richi Nayak

Addresses: Science and Engineering Faculty, Queensland University of Technology, Brisbane, Queensland, CBD QLD 4001, Australia; Department of Transport and Main Roads, P.O. Box 673, Fortitude Valley, Queensland, QLD 4006, Australia ' Science and Engineering Faculty, Queensland University of Technology, Brisbane, Queensland, CBD QLD 4001, Australia; Department of Transport and Main Roads, P.O. Box 673, Fortitude Valley, Queensland, QLD 4006, Australia ' Science and Engineering Faculty, Queensland University of Technology, Brisbane, Queensland, CBD QLD 4001, Australia; Department of Transport and Main Roads, P.O. Box 673, Fortitude Valley, Queensland, QLD 4006, Australia ' Science and Engineering Faculty, Queensland University of Technology, Brisbane, Queensland, CBD QLD 4001, Australia; Department of Transport and Main Roads, P.O. Box 673, Fortitude Valley, Queensland, QLD 4006, Australia

Abstract: Road networks are a national critical infrastructure. The road assets need to be monitored and maintained efficiently as their conditions deteriorate over time. The condition of one of such assets, road pavement, plays a major role in the road network maintenance programmes. Pavement conditions depend upon many factors such as pavement types, traffic and environmental conditions. This paper presents a data analytics case study for assessing the factors affecting the pavement deflection values measured by the traffic speed deflectometer (TSD) device. The analytics process includes acquisition and integration of data from multiple sources, data pre-processing, mining useful information from them and utilising data mining outputs for knowledge deployment. Data mining techniques are able to show how TSD outputs vary in different roads, traffic and environmental conditions. The generated data mining models map the TSD outputs to some classes and define correction factors for each class.

Keywords: data mining; classification; road pavement deflection; critical infrastructures; roads; road networks; road maintenance; traffic speed deflectometer; data analysis.

DOI: 10.1504/IJBIDM.2013.059024

International Journal of Business Intelligence and Data Mining, 2013 Vol.8 No.3, pp.199 - 226

Published online: 28 Jun 2014 *

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