In order to help the decisions makers to efficiently address eco-design for transport infrastructure technologies, a decision support toll (DST) was developed in the scope of the training-through-research programme Sustainable Pavements & Railways Initial Training Network (www.superitn.eu). It consists of a computational platform that implements a conceptual framework developed to quantify sustainability. It comes with a set of sustainability in-dicators tailored to both road and railway systems as well as several objective and subjective weighting methods. Amongst those belonging to the last category, the DST includes a set of default weights derived from an Analyt-ical Hierarchy Process (AHP)-based survey that engaged stakeholders from different sectors and from several European countries. At last, the Preference Ranking Organization Methodology of Enrichment Evaluation II (PROMETHEE-II) MCDM method is employed for prioritizing alternative road pavement and railway tracks solutions at the design stage. The SUP&R DST is a freely available upon request (http://superitn.eu) and can be used at professional level, by professionals interested in advancing sustainability in transportation, as well as for educational purposes, to provide knowledge and educate on the use sustainability concepts and on what are the important issues to consider during the sustainable transportation decision-making process.

Santos, J., Bressi, S., Cerezo, V., Lo Presti, D. (2019). SUP&R DST: SUstainable pavement & railways decision support tool. In R. Edited by: Caspeele, L. Taerwe, D.M. Frangopol (a cura di), Life Cycle Analysis and Assessment in Civil Engineering: Towards an Integrated Vision - Proceedings of the 6th International Symposium on Life-Cycle Civil Engineering, IALCCE 2018 (pp. 1653-1660).

SUP&R DST: SUstainable pavement & railways decision support tool

Lo Presti, D.
2019-01-01

Abstract

In order to help the decisions makers to efficiently address eco-design for transport infrastructure technologies, a decision support toll (DST) was developed in the scope of the training-through-research programme Sustainable Pavements & Railways Initial Training Network (www.superitn.eu). It consists of a computational platform that implements a conceptual framework developed to quantify sustainability. It comes with a set of sustainability in-dicators tailored to both road and railway systems as well as several objective and subjective weighting methods. Amongst those belonging to the last category, the DST includes a set of default weights derived from an Analyt-ical Hierarchy Process (AHP)-based survey that engaged stakeholders from different sectors and from several European countries. At last, the Preference Ranking Organization Methodology of Enrichment Evaluation II (PROMETHEE-II) MCDM method is employed for prioritizing alternative road pavement and railway tracks solutions at the design stage. The SUP&R DST is a freely available upon request (http://superitn.eu) and can be used at professional level, by professionals interested in advancing sustainability in transportation, as well as for educational purposes, to provide knowledge and educate on the use sustainability concepts and on what are the important issues to consider during the sustainable transportation decision-making process.
2019
978-113862633-1
Santos, J., Bressi, S., Cerezo, V., Lo Presti, D. (2019). SUP&R DST: SUstainable pavement & railways decision support tool. In R. Edited by: Caspeele, L. Taerwe, D.M. Frangopol (a cura di), Life Cycle Analysis and Assessment in Civil Engineering: Towards an Integrated Vision - Proceedings of the 6th International Symposium on Life-Cycle Civil Engineering, IALCCE 2018 (pp. 1653-1660).
File in questo prodotto:
File Dimensione Formato  
full_paper_0519_submitter_0553_LoPresti_Davide - revise_JS.pdf

Solo gestori archvio

Tipologia: Pre-print
Dimensione 525.4 kB
Formato Adobe PDF
525.4 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/417406
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact