Predictive and prescriptive analytics in transportation geotechnics: Three case studies

Tinoco, Joaquim; Parente, Manuel; Gomes Correia, António; Cortez, Paulo; Toll, David

Abstract

Transportation infrastructure is of paramount importance for any country. The construction, management and maintenance of this infrastructure is a complex task that requires a significant amount of resources (e.g., human work equipment, materials, maintenance costs). To better support this task, in the last decades several Artificial Intelligence (AI) data analysis tools have been proposed. In this paper, we summarize recent predictive and prescriptive AI applications to the transportation infrastructure field, underlying their strategic impact. In particular, we discuss three case studies: the design of better earthwork projects; the prediction of jet grouting soilcrete mechanical and physical properties (uniaxial compressive strength, stiffness and column diameter); and prediction of the stability level of engineered slopes.

Citation

Tinoco, J., Parente, M., Gomes Correia, A., Cortez, P., & Toll, D. (2021). Predictive and prescriptive analytics in transportation geotechnics: Three case studies. Transportation Engineering, 5, Article 100074. https://doi.org/10.1016/j.treng.2021.100074

• Journal Article Type: Article
• Acceptance Date: May 19, 2021
• Online Publication Date: Jun 1, 2021
• Publication Date: 2021-09
• Deposit Date: Dec 5, 2022
• Journal: Transportation Engineering
• Electronic ISSN: 2666-691X
• Publisher: Elsevier
• Volume: 5
• Article Number: 100074
• DOI: https://doi.org/10.1016/j.treng.2021.100074
• Public URL: https://durham-repository.worktribe.com/output/1187632