  Travel mode detection has been a hot topic in the field of GPS
trajectory-related processing. Former scholars have developed many mathematical
methods to improve the accuracy of detection. Among these studies, almost all
of the methods require ground truth dataset for training. A large amount of the
studies choose to collect the GPS trajectory dataset for training by their
customized ways. Currently, there is no open GPS dataset marked with travel
mode. If there exists one, it will not only save a lot of efforts in model
developing, but also help compare the performance of models. In this study, we
propose and open GPS trajectory dataset marked with travel mode and benchmark
for the travel mode detection. The dataset is collected by 7 independent
volunteers in Japan and covers the time period of a complete month. The travel
mode ranges from walking to railway. A part of routines are traveled repeatedly
in different time slots to experience different road and travel conditions. We
also provide a case study to distinguish the walking and bike trips in a
massive GPS trajectory dataset.
