Symbolization and data mining of multi-modal signals using Bag of Systems
Chihiro Sannomiya, Yusuke Zn Tanaka, Hironori Kamakura, Keisuke Kurihara, Ryo Neyama, Kazunari Nawa · 2016
In this report, we discuss about a data mining method for multi-modal in-vehicle sensor signals. Though several methods were previously proposed for symbolization of the multi-modal in-vehicle signals, the effectiveness of such method were not discussed in detail. We adopt the Bag-of-System (BoS) technique, a variation of the Bag-of-Features for sensor signals used in motion analysis, and evaluate the effectiveness for several complicated scenarios. According to the requirement of realistic practical data analysis, we extend the BoS technique and evaluate for scenarios such as lane change detection and turning estimation. According to the evaluation of the simple case, three behaviors at the intersections are successfully estimated. However, the technique exhibited lower performance for a complicated behavior such as lane change.