Identifying types of staying facilities from traffic behavior log data

Yu Sugawara, Takeshi Morita, Hidenao Abe, Shuichi Matsumoto, Takahira Yamaguchi

Research output: Contribution to journalConference article

Abstract

Traffic 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.

Original languageEnglish
Pages (from-to)1495-1504
Number of pages10
JournalProcedia Computer Science
Volume35
Issue numberC
DOIs
Publication statusPublished - 2014 Jan 1
EventInternational Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2014 - Gdynia, Poland
Duration: 2014 Sep 152014 Sep 17

Keywords

  • Automation
  • Log Data
  • Person Trip Survey
  • Positional Data
  • Traffic Behavior Survey

ASJC Scopus subject areas

  • Computer Science(all)

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