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Conference object . 2018
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Big data for low-carbon transport: an overview of applications for designing the future of road and air transport

Authors: Michele De Gennaro; Alessandro Zanon; Helmut Kuehnelt; Marco Pretto; Pietro Giannattasio;

Big data for low-carbon transport: an overview of applications for designing the future of road and air transport

Abstract

Big data is one of the most promising research trends of this decade, and navigation data allows for unprecedented opportunities for designing future low-carbon transportation infrastructures. This paper presents two applications based on navigation data in the fields of road and air transport. The first application shows how driving patterns from conventional fuel vehicles can be used for developing real-world scenario analyses for deploying hybrid and electric vehicles, quantifying their energy demand on the electric grid and the infrastructure needed to serve it. Moreover, results of the real-world driving and non-driving emissions from conventional vehicles are also presented, adopting as example the Italian province of Firenze. The second application shows how flight pattern data can be combined with noise emission models to quantify the real-world noise impact of civil air operation. The computed sound levels allow for drawing real-world noise maps and three airports have been chosen as examples: a small aerodrome (Trieste), and two intercontinental hubs (Vienna Schwechat and London Heathrow).

Keywords

big data; low-carbon transport; navigation data; electric vehicles; noise maps; road transport; air transport;

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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