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An Intelligent Visualisation Tool to Analyse the Sustainability of Road Transportation

Author

Listed:
  • Carlos Alonso de Armiño

    (Departamento de Ingeniería de Organización, Escuela Politécnica Superior, Universidad de Burgos, Av. Cantabria S/N, 09006 Burgos, Spain)

  • Daniel Urda

    (Grupo de Inteligencia Computacional Aplicada-GICAP, Departamento de Ingeniería Informática, Escuela Politécnica Superior, Universidad de Burgos, Av. Cantabria S/N, 09006 Burgos, Spain)

  • Roberto Alcalde

    (Departamento de Economía y Administración de Empresas, Facultad de Ciencias Económicas y Empresariales, Universidad de Burgos, Pza. de la Infanta Dª. Elena, S/N, 09001 Burgos, Spain)

  • Santiago García

    (Departamento de Ingeniería de Organización, Escuela Politécnica Superior, Universidad de Burgos, Av. Cantabria S/N, 09006 Burgos, Spain)

  • Álvaro Herrero

    (Grupo de Inteligencia Computacional Aplicada-GICAP, Departamento de Ingeniería Informática, Escuela Politécnica Superior, Universidad de Burgos, Av. Cantabria S/N, 09006 Burgos, Spain)

Abstract

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.

Suggested Citation

  • Carlos Alonso de Armiño & Daniel Urda & Roberto Alcalde & Santiago García & Álvaro Herrero, 2022. "An Intelligent Visualisation Tool to Analyse the Sustainability of Road Transportation," Sustainability, MDPI, vol. 14(2), pages 1-15, January.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:2:p:777-:d:722177
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    References listed on IDEAS

    as
    1. Shankar, Ravi & Pathak, Devendra Kumar & Choudhary, Devendra, 2019. "Decarbonizing freight transportation: An integrated EFA-TISM approach to model enablers of dedicated freight corridors," Technological Forecasting and Social Change, Elsevier, vol. 143(C), pages 85-100.
    2. Kelle, Peter & Song, Jinglu & Jin, Mingzhou & Schneider, Helmut & Claypool, Christopher, 2019. "Evaluation of operational and environmental sustainability tradeoffs in multimodal freight transportation planning," International Journal of Production Economics, Elsevier, vol. 209(C), pages 411-420.
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    Cited by:

    1. Claudia-Elena GRIGORAS-ICHIM & Alexandra-Valentina PETRESCU, 2022. "Comparison Of The Cost Of Road Transport Of Goods In Romania And Germany," European Journal of Accounting, Finance & Business, "Stefan cel Mare" University of Suceava, Romania - Faculty of Economics and Public Administration, West University of Timisoara, Romania - Faculty of Economics and Business Administration, vol. 10(3), pages 25-34, October.

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