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Artificial Intelligence–Based Decision Support Technologies in Pavement Management
Author(s) -
Sundin Sten,
BrabanLedoux Corinne
Publication year - 2001
Publication title -
computer‐aided civil and infrastructure engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.773
H-Index - 82
eISSN - 1467-8667
pISSN - 1093-9687
DOI - 10.1111/0885-9507.00220
Subject(s) - computer science , decision support system , identification (biology) , process (computing) , field (mathematics) , pavement management , fuzzy logic , expert system , artificial neural network , selection (genetic algorithm) , genetic programming , artificial intelligence , systems engineering , engineering , transport engineering , botany , mathematics , pure mathematics , biology , operating system
The field of road pavement engineering has seen an explosion of artificial intelligence–based applications since the late 1980s. Such applications are found at key stages of the decision process involved in pavement management. In the analysis phase, they perform pavement diagnosis and deterioration modeling tasks. In the design phase, they enable rehabilitation needs to be assessed and contribute to the identification and selection of maintenance actions. Finally, in the choice phase, they are applied for priority programming of rehabilitation and maintenance. They either represent alternative approaches to existing systems or collaborate to make the overall system more efficient. The purpose of this article is to summarize the findings of up‐to‐date research articles concerning the application of artificial intelligence to pavement management and to illustrate the potential such tools can offer to pavement engineers. Artificial intelligence techniques include expert systems, artificial neural networks, fuzzy logic, genetic algorithms, and hybrid systems.