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.
翻译:在全球定位系统轨迹相关处理领域,旅行模式探测一直是热门话题。前学者已经开发了许多数学方法来提高探测的准确性。在这些研究中,几乎所有方法都需要地面真相数据集进行培训。大量研究选择收集全球定位系统轨迹数据集,以便以定制方式进行培训。目前,没有带有旅行模式的开放全球定位系统数据集。如果存在,这不仅将节省模型开发方面的大量努力,而且还有助于比较模型的性能。在本研究中,我们提议并开放带有旅行模式和旅行模式探测基准标志的全球定位系统轨迹数据集。数据集由日本的7名独立志愿者收集,涵盖整个月的时间。旅行模式从步行到铁路不等。部分例行活动是在不同的时段反复进行,以体验不同的道路和旅行条件。我们还提供案例研究,以在大型全球定位系统轨迹数据集中区分行走和自行车旅行。