Using Smartphones to Capture Personal Travel Behavior

Using Smartphones to Capture Personal Travel Behavior

Sheila Ferrer (Universitat Politècnica de València, Spain) and Tomás Ruiz (Universitat Politècnica de València, Spain)
DOI: 10.4018/978-1-4666-6170-7.ch011
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Abstract

Embedded with a wide variety of sensors, such as GPSs, accelerometers, gyroscopes, and microphones, smartphones have become a very useful tool in the context of travel surveys. In this chapter, the authors present an innovative tool to estimate individuals' mobility patterns using an application for smartphones that records GPS and accelerometer data from trips annotated by the user. The authors also present a neural network model for the classification of trips into four transportation modes, based on features extracted from the accelerometer signal. A small sample was collected in Valencia (Spain) to train and evaluate the model. The best classification results were achieved for detecting walking trips (98.2%) and bike rides (99.3%).
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Background

Using smartphones is generally cheaper, faster and more accurate than conventional methods for collecting activity-travel information. Additionally, smartphone-based data collection methods are less of a burden to respondents, compared to paper-based and telephone-based surveys.

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