EventsOHOW 2022 – The 1st International Symposium on One Health, One World
Event submissions
Published
with-doi10.3390/ohow2022-13616 (registering DOI)
This submission belongs to the session S1. Urban Safety and Disaster Mitigation of the event OHOW 2022 – The 1st International Symposium on One Health, One World
Published date
16 Nov, 2022
Academic Editor
author-avatarWataru Takeuchi
Citation
Yuta Arakawa, Kazuyuki Takada, DETECTION OF ABNORMAL DRIVING APPLYING RECURRENCE PLOTS, in Proceedings of OHOW 2022 – The 1st International Symposium on One Health, One World, Amari Pattaya Hotel, 8 December–10 December 2022, MDPI: Basel, Switzerland, doi: 10.3390/ohow2022-13616
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DETECTION OF ABNORMAL DRIVING APPLYING RECURRENCE PLOTS

Yuta Arakawa 1
Kazuyuki Takada 2
1. Tokyo Denki University, Japan
2. Tokyo Denki University
Abstract

In Japan, the number of traffic accidents caused by elderly drivers is increasing. The National Police Agency of Japan requires elderly drivers over the age of 75 to　have a cognitive impairment test to check their ability of driving aptitude. However, it is difficult to prevent the occurrence of traffic accidents among the elderly by these measures alone. It is necessary for each elderly driver to understand his or her own driving skills and to take appropriate measures.

In this study, a recurrence plot was created from driving behavior data, and a deep learning image recognition technique was applied to detect abnormal driving.

Keywords
elderly driver
probe data
recurrence plot
anomaly detection
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