Cell Phone Enabled Travel Surveys: The Medium Moves the Message

Abstract Purpose — To assess how cell phone technology might impact the collection of travel data in the future. Design/methodology/approach — Two different types of cell phone enabled studies are considered. First, we examine how the text feature of phones can be used for person-to-person surveys, and second, we explore an aggregate level survey enabled by an anonymous and passive GPS trace. Findings — This study explores the types of travel information that are likely to be inferred from text surveys and cell phone traces. It recognizes that a passive GPS trace might change the level of measurement and the inferences we make about travel behaviors. Research limitations/implications — The study is prospective. It anticipates that over the next 10–15 years cell phone tracking technology will improve, as well as the speed and capability of algorithms for post-processing the information. Practical implications — Cell phone enabled studies may provide a new tool and new level of measurement, as traditional survey response rates decline, and it becomes more difficult and expensive to conduct conventional travel surveys. The capacity of cell phones for travel survey work is improving, but it is not fully realizable today (2012). Originality/value — This study provides a context to understand how the technology of the cell phone might be integrated with more traditional travel surveys to streamline data collection, and produce new types of spatial detection, measurement, and tracking.

[1]  Murat Ali Bayir,et al.  A Web-Based Personalized Mobility Service for Smartphone Applications , 2011, Comput. J..

[2]  Harry Timmermans,et al.  Ubiquitous travel environments and travel control strategies : Prospects and challenges , 2010 .

[3]  Sean T. Doherty,et al.  Data Collection on Personal Movement using Mobile ICTs: Old Wine in New Bottles? , 2010 .

[4]  Caroline J Rodier,et al.  Transit-based smart parking: An evaluation of the San Francisco Bay area field test , 2010 .

[5]  Antti Oulasvirta,et al.  Grounding the innovation of future technologies , 2005 .

[6]  Yasuo Asakura,et al.  Simulating Travel Behaviour using Location Positioning Data Collected with A Mobile Phone System , 2005 .

[7]  Daniele Quercia,et al.  Mobile Phones and Outdoor Advertising: Measurable Advertising , 2011, IEEE Pervasive Computing.

[8]  Andrew S Harvey,et al.  Non-Web Technologies , 2006 .

[9]  Yasuo Asakura,et al.  TRACKING SURVEY FOR INDIVIDUAL TRAVEL BEHAVIOUR USING MOBILE COMMUNICATION INSTRUMENTS , 2004 .

[10]  Jon A. Krosnick,et al.  Research Synthesis AAPOR Report on Online Panels , 2010 .

[11]  Carlo Ratti,et al.  Eigenplaces: Analysing Cities Using the Space–Time Structure of the Mobile Phone Network , 2009 .

[12]  Carlo Ratti,et al.  Cellular Census: Explorations in Urban Data Collection , 2007, IEEE Pervasive Computing.

[13]  Peter R. Stopher,et al.  The Travel Survey Toolkit: Where to From Here? , 2009 .

[14]  Satoshi Fujii,et al.  TIME-USE DATA, ANALYSIS AND MODELING: TOWARD THE NEXT GENERATION OF TRANSPORTATION PLANNING METHODOLOGIES , 1997 .

[15]  Margaret Martonosi,et al.  Identifying Important Places in People's Lives from Cellular Network Data , 2011, Pervasive.

[16]  Ryuichi Kitamura,et al.  Micro-simulation of daily activity-travel patterns for travel demand forecasting , 2000 .

[17]  Deborah Estrin,et al.  Using mobile phones to determine transportation modes , 2010, TOSN.

[18]  Frank van der Hoeven Setting the Stage for the Integration of Demand Responsive Transport and Location-Based Services , 2010 .

[19]  Marcus Wigan,et al.  Transport and Surveillance Aspects of Location-Based Services , 2009 .

[20]  Nitesh V. Chawla,et al.  Enhanced Situational Awareness: Application of DDDAS Concepts to Emergency and Disaster Management , 2007, International Conference on Computational Science.

[21]  Peter R. Stopher,et al.  Collecting and Processing Data from Mobile Technologies , 2009 .

[22]  Courtney Kennedy,et al.  Use of Cognitive Shortcuts in Landline and Cell Phone Surveys , 2011 .

[23]  Raja Sengupta,et al.  The connected traveler: using location and personalization on mobile devices to improve transportation , 2009, LOCWEB '09.

[24]  Carlo Ratti,et al.  Mobile Landscapes: Using Location Data from Cell Phones for Urban Analysis , 2006 .