Title
Detecting Air Travel To Survey Passengers On A Worldwide Scale
Abstract
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' behaviour that can eventually provide original insights into mobility studies. Because these technologies can capture travellers' experience in context and real time, they pave the road for new survey methods. In this article, we demonstrate that mobile phones can recognise air travel with a light algorithm that scans their connectivity to cellular networks. The originality of our 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 travellers 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 centralised server. This approach respects the traveller's privacy and proved a 97% success rate in detecting flights in a 12-months study involving six travellers who boarded on 76 planes.
Year
DOI
Venue
2009
10.1080/17489720903339676
JOURNAL OF LOCATION BASED SERVICES
Keywords
Field
DocType
sensing and activity recognition, mobility detection, transportation study
Travel behavior,Wireless,Telecommunications,Computer science,Originality,Cellular network,Global Positioning System,Recall bias,Survey methodology,Market research
Journal
Volume
Issue
ISSN
3
3
1748-9725
Citations 
PageRank 
References 
1
0.35
11
Authors
3
Name
Order
Citations
PageRank
Fabien Girardin110910.06
Pierre Dillenbourg21825183.19
Nicolas Nova3879.65