Identifying Types of Staying Facilities from Traffic Behavior Log Data

AbstractTraffic behavior surveys by hand require both a lot of money and human resources. Recently, traffic behavior surveys using information technology have been carried out. In this study, we propose a method to extract staying points from GPS-based positional data and identify the types of staying facilities by using Google Places API, a facility ontology, the regularity which is analyzed from trip chains about traffic behavior. This method could identify 68.5% types of staying facilities correctly in the evaluation using GPS location data from the Traffic Behavior Survey in Nagasaki