Open AccessArtificial Neural Networks in Pavement Engineering: A Recent Review
Author(s) -
A. J. Kurian,
Elvin Sunildutt
Publication year - 2021
Publication title -
aijr proceedings
Language(s) - English
Resource type - Conference proceedings
ISSN - 2582-3922
DOI - 10.21467/proceedings.112.66
Subject(s) - pavement management , pavement engineering , artificial neural network , schedule , engineering , civil engineering , field (mathematics) , traffic engineering , computer science , deep learning , construction engineering , transport engineering , artificial intelligence , cartography , mathematics , asphalt , pure mathematics , geography , operating system
The application of Artificial Neural Networks (ANN) in civil engineering has increased drastically in the past few years. ANN tools are nowadays used commonly in developed countries over various fields of civil engineering like geotechnical, structural, traffic, pavement engineering etc. This paper deals with the review of recent advancements and utilization of ANNs in pavement engineering. The review will focus on pavement performance prediction, maintenance strategies, distress intensity detection through deep learning techniques, pavement condition index prediction etc. The use of ANNs in pavement management systems are expected to furnish a systematic schedule and economic management strategies in the field of pavement engineering. The use of ANNs combined with deep learning techniques help to address complex problems in pavement engineering and pave the way to a sustainable future.