Bicycle behavior recognition using sensors equipped with smartphone

Yuri Usami, Kazuaki Ishikawa, Toshinori Takayama, Masao Yanagisawa, Nozomu Togawa

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

1 Citation (Scopus)

Abstract

It becomes possible to prevent accidents beforehand by predicting dangerous riding behavior based on recognition of bicycle behaviors. In this paper, we propose a bicycle behavior recognition method using a three-axis acceleration sensor and three-axis gyro sensor equipped with a smartphone. We focus on the periodic handlebar motions for balancing while running a bicycle and reduce the sensor noises caused by them. After that, we use machine learning for recognizing the bicycle behaviors, effectively utilizing the motion features in bicycle behavior recognition. The experimental results demonstrate that the proposed method accurately recognizes the four bicycle behaviors of stop, run straight, turn right, and turn left and its F-measure becomes around 0.9 while the F-measure of the existing method just reaches 0.6-0.8.

Original languageEnglish
Title of host publication2018 IEEE 8th International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2018
PublisherIEEE Computer Society
ISBN (Electronic)9781538660959
DOIs
Publication statusPublished - 2018 Dec 13
Event8th IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2018 - Berlin, Germany
Duration: 2018 Sep 22018 Sep 5

Publication series

NameIEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin
Volume2018-September
ISSN (Print)2166-6814
ISSN (Electronic)2166-6822

Other

Other8th IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2018
CountryGermany
CityBerlin
Period18/9/218/9/5

Keywords

  • acceleration sensor
  • behavior recognition
  • bicycle
  • gyro sensor
  • smartphone

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Industrial and Manufacturing Engineering
  • Media Technology

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