Detecting Air Travel to Survey Passengers on a Worldwide Scale

Market research in the transportation sector is often based on traditional surveys, such as travel diaries, which have well-documented shortcomings and biases. The advent of mobile and wireless technologies enables new methods of investigation of passengers' behavior that can eventually provide original insights into mobility studies. Because these technologies can capture travelers' experience in context and real time, they pave the road for new survey methods. In this article, it is demonstrated that mobile phones can recognize air travel with a light algorithm that scans their connectivity to cellular networks. The originality of the method is that it does not rely on any Global Positioning System-like location information and runs on a large variety of mobile phones. It detects flights on a worldwide scale and asks travelers to report on their travel experiences as they occur, eliminating the recall bias of traditional solutions. Once the system detects a journey, it triggers a flight satisfaction questionnaire that sends answers to a centralized server. This approach respects the traveler's privacy and proved a 97% success rate in detecting flights in a 12-months study involving six travelers who boarded on 76 planes.

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  • Supplemental Notes:
    • Abstract reprinted with permission from Taylor and Francis
  • Authors:
    • Girardin, Fabien
    • Dillenbourg, Pierre
    • Nova, Nicolas
  • Publication Date: 2009-9

Language

  • English

Media Info

Subject/Index Terms

Filing Info

  • Accession Number: 01149212
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Jan 27 2010 6:16PM