RT info:eu-repo/semantics/article T1 An Intelligent Visualisation Tool to Analyse the Sustainability of Road Transportation A1 Alonso de Armiño Pérez, Carlos A1 Urda Muñoz, Daniel A1 Alcalde Delgado, Roberto A1 García Pineda, Santiago A1 Herrero Cosío, Álvaro K1 Artificial intelligence K1 Unsupervised machine learning K1 Exploratory projection pursuit K1 Clustering K1 Road transportation K1 Transport sustainability K1 Age of transport means K1 Transporte K1 Transportation K1 Informática K1 Computer science AB Road transport is an integral part of economic activity and is therefore essential for its development. On the downside, it accounts for 30% of the world’s GHG emissions, almost a third of which correspond to the transport of freight in heavy goods vehicles by road. Additionally, means of transport are still evolving technically and are subject to ever more demanding regulations, which aim to reduce their emissions. In order to analyse the sustainability of this activity, this study proposes the application of novel Artificial Intelligence techniques (more specifically, Machine Learning). In this research, the use of Hybrid Unsupervised Exploratory Plots is broadened with new Exploratory Projection Pursuit techniques. These, together with clustering techniques, form an intelligent visualisation tool that allows knowledge to be obtained from a previously unknown dataset. The proposal is tested with a large dataset from the official survey for road transport in Spain, which was conducted over a period of 7 years. The results obtained are interesting and provide encouraging evidence for the use of this tool as a means of intelligent analysis on the subject of developments in the sustainability of road transportation. PB MDPI SN 2071-1050 YR 2022 FD 2022-01 LK http://hdl.handle.net/10259/6634 UL http://hdl.handle.net/10259/6634 LA eng DS Repositorio Institucional de la Universidad de Burgos RD 29-mar-2024