A Review of Automatic Travel Mode Detection Methods

Abstract

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.