A driver situational awareness estimation system based on standard glance model for unscheduled takeover situations

Hiroaki Hayashi, Mitsuhiro Kamezaki, Udara E. Manawadu, Takahiro Kawano, Takaaki Ema, Tomoya Tomita, Lollett Catherine, Shigeki Sugano

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

1 Citation (Scopus)

Abstract

Highly-automated vehicles operating in level 3 issue a takeover request (TOR) to transfer the control authority from the autonomated driving (AD) system to a human driver when they encounter system limitations. In such 'unscheduled' situations, the driver is required to immediately re-engage in the driving task both physically and cognitively, and perform suitable action, e.g. lane change. Thus, evaluating driver engagement by the AD system would lead to safe takeover. Physical engagement is easily estimated but there are few studies on evaluating cognitive engagement. In this study, we thus developed a driver situational awareness estimation system based on glance information. We first defined seven standard glance areas and driver glance classification model using a convolutional neural network. We then obtained a large amount of glance data when both safe and dangerous takeover situations (lane change) by using a driving simulator, and we derived the standard glance model including the glance area and time, in order to estimate whether driver gained enough cognitive re-engagement in real-time. To evaluate the effectiveness of the proposed model, we created a situational awareness assist system to visually indicate regions with insufficient glance. As a result, we found that the assist system drastically improved driving performance and reduced the number of accidents during takeover.

Original languageEnglish
Title of host publication2019 IEEE Intelligent Vehicles Symposium, IV 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages798-803
Number of pages6
ISBN (Electronic)9781728105604
DOIs
Publication statusPublished - 2019 Jun 1
Event30th IEEE Intelligent Vehicles Symposium, IV 2019 - Paris, France
Duration: 2019 Jun 92019 Jun 12

Publication series

NameIEEE Intelligent Vehicles Symposium, Proceedings
Volume2019-June

Conference

Conference30th IEEE Intelligent Vehicles Symposium, IV 2019
CountryFrance
CityParis
Period19/6/919/6/12

ASJC Scopus subject areas

  • Computer Science Applications
  • Automotive Engineering
  • Modelling and Simulation

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