Modeling the effects of auditory display takeover requests on drivers’ behavior in autonomous vehicles

Sangjin Ko, Yiqi Zhang, Myounghoon Jeon

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

1 Scopus citations

Abstract

In semi-autonomous vehicles (SAE level 3) that require driver’s engagement in critical situations, it is important to secure reliable control transitions. There have been many studies on investigating appropriate auditory displays for takeover request (TOR) but most of them were empirical experiments. In the present study, we established two computational models using a Queuing Network Model Human Processor (QN-MHP) framework to predict a driver’s reaction time to auditory displays for TOR. The reaction time for different sound types were modeled based on the results of subjective questionnaire in empirical studies. Separately, the reaction times for various non-speech sounds were modeled by using acoustical characteristics of sounds and previous empirical studies. It is one of a few attempts modeling the effects of auditory displays for TOR on the reaction time in autonomous driving. The current study will contribute to driving research by allowing us to simulate and predict drivers’ behavior.

Original languageEnglish (US)
Title of host publicationAdjunct Proceedings - 11th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, AutomotiveUI 2019
PublisherAssociation for Computing Machinery, Inc
Pages392-398
Number of pages7
ISBN (Electronic)9781450369206
DOIs
StatePublished - Sep 21 2019
Event11th ACM International Conference on Automotive User Interfaces and Interactive Vehicular Applications, AutomotiveUI 2019 - Utrecht, Netherlands
Duration: Sep 21 2019Sep 25 2019

Publication series

NameAdjunct Proceedings - 11th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, AutomotiveUI 2019

Conference

Conference11th ACM International Conference on Automotive User Interfaces and Interactive Vehicular Applications, AutomotiveUI 2019
CountryNetherlands
CityUtrecht
Period9/21/199/25/19

All Science Journal Classification (ASJC) codes

  • Automotive Engineering
  • Artificial Intelligence

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