Identifying behaviour objective from traffic behaviour log data by using facility ontology

Yu Sugawara, Takeshi Morita, H. Abe, Shuichi Matsumoto, Takahira Yamaguchi
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Abstract

Traffic behaviour surveys by hand require both a lot of money and human resources. Recently, traffic behaviour surveys using information technology have been carried out. In this study, we propose a method to extract staying points from GPS-based positional data, to identify the types of staying facilities by using Google Places API, a facility ontology, the regularity which is analysed from trip chains about traffic behaviour and to determine the behaviour objectives based on the rules between the behaviour objectives and the types of staying facilities. This method could identify 67.9% behaviour objectives in the evaluation using GPS location data from the traffic behaviour survey in Nagasaki.
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利用设施本体从交通行为日志数据中识别行为目标
手工进行交通行为调查需要大量的资金和人力资源。最近,我们利用资讯科技进行交通行为调查。在本研究中,我们提出了一种从基于gps的位置数据中提取停留点的方法,通过使用Google Places API(设施本体)从出行链中分析交通行为的规律性来识别住宿设施的类型,并根据行为目标与住宿设施类型之间的规则来确定行为目标。利用长崎市交通行为调查的GPS定位数据,该方法可识别出67.9%的行为目标。
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