Passenger-Centric Metrics for Air Transportation Leveraging Mobile Phone and Twitter Data
Autor: | Eric Feron, Philippe Monmousseau, Aude Marzuoli |
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Přispěvatelé: | Georgia Institute of Technology [Atlanta], Ecole Nationale de l'Aviation Civile (ENAC) |
Jazyk: | angličtina |
Rok vydání: | 2018 |
Předmět: |
050210 logistics & transportation
Aviation business.industry Computer science 05 social sciences Perspective (graphical) ComputerApplications_COMPUTERSINOTHERSYSTEMS 02 engineering and technology Air transportation system Transport engineering Mobile phone Scale (social sciences) 0502 economics and business ComputerApplications_GENERAL 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC] business |
Zdroj: | ICDMW 2018, IEEE International Conference on Data Mining Workshops ICDMW 2018, IEEE International Conference on Data Mining Workshops, Nov 2018, Singapour, Singapore. ⟨10.1109/ICDMW.2018.00091⟩ ICDM Workshops |
DOI: | 10.1109/ICDMW.2018.00091⟩ |
Popis: | International audience; This paper aims at presenting a detailed analysis of domestic air passengers behavior during a major air-traffic disturbance, from two complementary passenger-centric perspective: a passenger mobility perspective and a passenger social media perspective. By leveraging over 5 billion records of mobile phone location data per day from a major carrier in the United States, passenger mobility can be reliably analyzed, no matter which airline the passengers fly on or which airport they fly to and from. Such information is currently unavailable to the major aviation stakeholders at such scale and can be used to establish performance benchmarks from a passenger's perspective. Combining it with a Twitter analysis provides a more detailed and passenger-focused analysis than the traditional flight-centric measurements used to evaluate the overall system performance. More generally, these two passenger-centric analysis could be implemented in real-time for a daily evaluation of the Air Transportation System, enabling a faster analysis of the impact of major disruptions, whether due to meteorological conditions or system failures. |
Databáze: | OpenAIRE |
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