Cookies on this website
We use cookies to ensure that we give you the best experience on our website. If you click 'Continue' we'll assume that you are happy to receive all cookies and you won't see this message again. Click 'Find out more' for information on how to change your cookie settings.

Traditionally, health researchers have used large-scale travel surveys to measure existing travel behavior and identify the determinants driving it. However, such surveys rely on self-reporting, which can be unreliable. Here, the authors discuss using wearable cameras that capture first-person point-of-view images to help objectively identify the duration, frequency, and mode of journeys and reveal potential errors inherent in self-reporting. Their approach could ultimately lead to a better understanding of the environments offering individuals opportunities to engage in more active forms of transportation. This column is part of a special issue on transit and transport. © 2002-2012 IEEE.

Original publication

DOI

10.1109/MPRV.2013.21

Type

Journal article

Journal

IEEE Pervasive Computing

Publication Date

04/02/2013

Volume

12

Pages

44 - 47