Quantification of Abrupt Driving Maneuver Utilizing ETC 2.0 Probe Data: A Case Study in Japan

Hodaka Matsushita, Takaki Hayashi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

As of the end of October 2017, the utilization of ETC 2.0 in Japan is about 15%, which is growing at a faster rate than its predecessor ETC1.0. ETC 2.0 probe data is designed to store new data fields, or features, such as position information history of the vehicle and abrupt driving maneuver history. Up to the present, the use of these data has not been well spreading, and the government of Japan supports the utilization of ETC 2.0 by the administrative and private enterprises. In this study, we aim to explore a new, effective use of ETC 2.0 probe data. The probe data is sizable, accumulating about 400 GB for one month. Analysis is conducted focusing on the number of abrupt driving maneuver in ten most popular tourist areas in the Greater Tokyo Area ('Kanto region') from April 2015 to March 2016. Using the ETC 2.0 probe data, we propose a methodology to quantify abrupt driving maneuver of individual drivers and to evaluate their driving behaviors with a view towards business applications in mind.

Original languageEnglish
Title of host publication8th International Conference on Logistics, Informatics and Service Sciences, LISS 2018 - Proceeding
EditorsXiaopu Shang, Guowei Hua, Dash Wu, Runtong Zhang, Juliang Zhang, Anqiang Huang
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538669655
DOIs
Publication statusPublished - 2018 Dec 27
Event8th International Conference on Logistics, Informatics and Service Sciences, LISS 2018 - Toronto, Canada
Duration: 2018 Aug 32018 Aug 6

Publication series

Name8th International Conference on Logistics, Informatics and Service Sciences, LISS 2018 - Proceeding

Conference

Conference8th International Conference on Logistics, Informatics and Service Sciences, LISS 2018
Country/TerritoryCanada
CityToronto
Period18/8/318/8/6

Keywords

  • Big data
  • ETC2.0
  • Sudden braking
  • Sudden steering
  • Zero-inflated Poisson regression model

ASJC Scopus subject areas

  • Strategy and Management
  • Computer Networks and Communications
  • Information Systems and Management
  • Control and Optimization

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