United States Department of Transportation
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Capturing the Relationship between Social Interaction and Travel Behavior Using Smart Phones
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2017-12-01
[PDF-621.06 KB]
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Edition:Year 25 Final Report
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Abstract:Humans are social beings, and as such their choices are affected by the way they interact with other people. Recent changes to the nature of social interaction have affected travel behavior and have led to an increasing interest in understanding the relationship between the two. Several studies have made efforts to model and quantify this relationship, mainly using pen-and-paper surveys, but very few of them collected data that are rich enough and over a time period long enough. Other studies used electronic devices [such as Global Positioning System (GPS) or smart phones] to collect more precise data, but mostly focused on one behavioral type at a time. The authors propose a methodology of data collection and modeling that combines recording of location and mode with a smart phone app [using GPS, Global System for Mobile Communications (GSM), WIFI and accelerometer], an egocentric approach for collecting social interaction data [using phone calls, Short Message Service (SMS) records, Bluetooth scans and Facebook activity], online questionnaires, and modeling of social interactions and travel behavior. This methodology leverages the techniques developed by the Singapore-MIT Alliance for Research and Technology (SMART/MIT) as part of the Future Mobility Sensing (FMS) project and the modeling expertise of the MIT ITS Lab. The authors anticipate that the results of this research will help policy makers learn how these changes may affect the decisions of individuals and plan accordingly. Social behavior and preferences may also affect people’s willingness to travel together, either with friends or with strangers. The results from this study can be used to understand and encourage usage of ridesharing services, and reduce congestion in the road network.
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