Development of an Abnormal Sign Detection System based on Driver Monitoring and Voice Interaction for Preventing Medical-Condition-Caused Car Accidents

Hiroaki Hayashi, Mitsuhiro Kamezaki, Naoki Oka, Shigeki Sugano

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

Abstract

The number of medical-condition-caused car accidents (MCCCAs) in transport industry (bus, truck, and taxi) recently increases. MCCCAs including cerebrovascular and cardiovascular disease lead to loss of consciousness, thus result in injury and loss of life, and heavy compensation payment. Toward this problem, conventional systems detect closing of eyes, and fallen down state as to prevent car collisions. However, the support is taken after driver losing consciousness. To prevent MCCCAs, it is important to find out abnormal signs before driver losing consciousness. It is challenging to detect abnormal signs not only early but also with high confidence level (CL). This paper proposes a novel method that multi-modally monitors driver to detect abnormal signs which can be cues for estimating a driving-disable state in future and performs voice interaction based on the result of monitoring to clarify the internal state of the driver. Considering no data of abnormal signs, this study developed the system using normal data and pseudo abnormal data, and method of outlier detection was used for abnormal signs detection. As results of experiment, we found the relationship between cue signs and CL, and the proposed system can detect 'sleepiness' state with accuracy of 80%. Voice interaction system did not increase driver's mental demand.

Original languageEnglish
Title of host publication2020 IEEE 23rd International Conference on Intelligent Transportation Systems, ITSC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728141497
DOIs
Publication statusPublished - 2020 Sep 20
Event23rd IEEE International Conference on Intelligent Transportation Systems, ITSC 2020 - Rhodes, Greece
Duration: 2020 Sep 202020 Sep 23

Publication series

Name2020 IEEE 23rd International Conference on Intelligent Transportation Systems, ITSC 2020

Conference

Conference23rd IEEE International Conference on Intelligent Transportation Systems, ITSC 2020
CountryGreece
CityRhodes
Period20/9/2020/9/23

ASJC Scopus subject areas

  • Artificial Intelligence
  • Decision Sciences (miscellaneous)
  • Information Systems and Management
  • Modelling and Simulation
  • Education

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