In recent years, the use of tracking apps has opened up new possibilities for recording people’s mobility behaviour. This offers many opportunities, but also harbours risks. This article analyses typical errors in app tracking data using an exploratory survey. Moreover, the methodological effects between a tracking app and a classic travel diary are compared on the basis of a quantitative survey. While the automatic recognition of the mode of transport by the app works very well overall, the automatic recognition of the activity or trip purpose in the app is very error prone. The use of the manual correction function is essential for correctly assigning activities. A conventional travel diary is more accurate for analysing activities. The segmentation into trip legs and stays by the tracking app is highly prone to errors in the case of short trip legs or stays. Sometimes, frequently occurring data gaps in the tracking process severely impair the quality of tracking data and can distort calculated parameters, such as journey time per day. Generally, the type and frequency of recording errors in the tracking app depend heavily on the mobility behaviour of the people surveyed.
Henkel et al. (Thu,) studied this question.