Application of an Artificial Neural Network in Pavement Management System

Scientific paper - Preliminary note / Short communication

• Author: Josipa Domitrović
• Author: Hrvoje Dragovan
• Author: Tatjana Rukavina
• Author: Sanja Dimter
• Author's institution: Josip Juraj Strossmayer University of Osijek; Faculty of Civil Engineering and Architecture Osijek; (Department for Geotechnics, Transportation and Geodesy)
• Author's institution: University of Zagreb; Faculty of Civil Engineering; (Transportation Engineering)
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Civil Engineering; Transportation

Abstract (english)

The era of intensive construction of new roads in Croatia is behind us. Today road agencies are focused on maintaining and preserving existing roads. Selection of an appropriate maintenance strategy is a complex task, which includes factors such as the current condition of the pavement, road classification, traffic volume etc. These factors are usually implemented in pavement management systems. The key components of pavement management systems are pavement performance prediction models such as artificial neural networks. This paper analyses the possibility of using artificial neural networks to evaluate existing pavement condition, and its possible application for defining the maintenance strategy of national roads. A backpropagation neural network was applied on 481.3 km of national roads in the Osijek-Baranja County. The obtained results indicated that artificial neural networks could be used for optimization of maintenance or rehabilitation strategies, and for the assessment of pavement condition at the project and network level.

• Keywords (english): artificial neural network; backpropagation algorithm; pavement maintenance; pavement management system
• Language: english
• Publication type: Scientific paper - Preliminary note / Short communication
• Publication status: Published
• Peer review: Peer review - international
• Publication version: Published version
• Journal title: Tehnicki vjesnik - Technical Gazette
• Numbering: vol. 25, no. Supplement 2, pp. 466-473
• p-ISSN: 1330-3651
• e-ISSN: 1848-6339
• DOI: https://doi.org/10.17559/TV-20150608121810
• URN:NBN: urn:nbn:hr:237:247361
• Publication: 2018
• Document URL: https://hrcak.srce.hr/205945
• Type of resource: Text
• Access conditions: Open access
• Created on: 2024-07-22 13:09:59