Driver classification in vehicle following behavior by using dynamic potential field method

Hanwool Woo, Yonghoon Ji, Yusuke Tamura, Yasuhide Kuroda, Takashi Sugano, Yasunori Yamamoto, Atsushi Yamashita, Hajime Asama

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

2 Citations (Scopus)

Abstract

In this paper, a novel method is proposed to classify drivers in vehicle following behavior. The main contribution of this work is to construct a method to classify drivers as the fundamental model to consider characteristics of each driver under a scene that the target vehicle follows the preceding vehicle. Many methods have been proposed using data-driven approaches, however, each driver has an own driving style and shows different characteristics to be influenced by traffic conditions. As the result, the performance of previous methods to detect common patterns trained by machine learning techniques may realize the limitation. The proposed method extracts a new feature to describe a driving style by using a dynamic potential field method, and it can be a significant feature to classify drivers. It is demonstrated that our new feature dramatically improves the accuracy of driver classification through experimental results.

Original languageEnglish
Title of host publication2017 IEEE 20th International Conference on Intelligent Transportation Systems, ITSC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
ISBN (Electronic)9781538615256
DOIs
Publication statusPublished - 2018 Mar 14
Externally publishedYes
Event20th IEEE International Conference on Intelligent Transportation Systems, ITSC 2017 - Yokohama, Kanagawa, Japan
Duration: 2017 Oct 162017 Oct 19

Publication series

NameIEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
Volume2018-March

Conference

Conference20th IEEE International Conference on Intelligent Transportation Systems, ITSC 2017
CountryJapan
CityYokohama, Kanagawa
Period17/10/1617/10/19

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

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