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Household trip data is of crucial importance for managing present transportation infrastructure as well as to
plan and design future facilities. It also provides basis for designing new policies, implemented under
Transportation Demand Management, and assessing their effectiveness. With passage of time, methods used
for household trip data collection have evolved, starting from the conventional face-to-face interviews or paperand-pencil interviews, moving on to mail-back surveys and internet-based surveys, before finally reaching to
the recent approach of passive data gathering. Recording travel data automatically will require the use of
modern technology present in the form of various sensors, and employing intelligent algorithms to infer the
required information from these sensors’ data. These sensors can be integrated into a purpose-built device or
more recently can be present in smartphones. The current study provides a comprehensive review of the
research done in the field of travel mode detection from data passively collected with the help of various devices.
The review starts from Global Positioning System (GPS) loggers and moves to cover purpose-built wearable
devices containing additional sensors and finally ending with the most modern approach of incorporating
smartphones. The summary tables presented in this study are of great value to the researchers trying to get
insight of this research field.
Muhammad Awais Shafique, Eiji Hato. (2020) A Review of Automatic Travel Mode Detection Methods , Mehran University Research Journal of Engineering & Technology, Volume 39, Issue 4.
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