Affective Driver State Monitoring for Personalized, Adaptive ADAS

Vijay Govindarajan, Katherine Driggs-Campbell, Ruzena Bajcsy

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

Abstract

We seek to improve vehicle automation by using the state of the driver to develop an adaptive assistance system. We focus on the problem of measuring the driver state under varying levels of cognitive workload using affective (i.e. emotion) sensing, including thermal facial analysis and electroencephalography (EEG). This information is then used in sensor fusion and machine learning algorithms to help predict the brake reaction time of the driver, a key input in forward collision warning systems. We demonstrate the results in a pilot study, which highlights the benefits of the personalized, adaptive reaction time estimation in collision warning alert performance. A 40-50% improvement in alert precision is observed with the adaptive approach. We conclude with improvements to further strengthen the quality of the reaction time estimation and improve alert performance.

Original languageEnglish (US)
Title of host publication2018 IEEE Intelligent Transportation Systems Conference, ITSC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1017-1022
Number of pages6
ISBN (Electronic)9781728103235
DOIs
StatePublished - Dec 7 2018
Event21st IEEE International Conference on Intelligent Transportation Systems, ITSC 2018 - Maui, United States
Duration: Nov 4 2018Nov 7 2018

Publication series

NameIEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
Volume2018-November

Other

Other21st IEEE International Conference on Intelligent Transportation Systems, ITSC 2018
CountryUnited States
CityMaui
Period11/4/1811/7/18

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

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  • Cite this

    Govindarajan, V., Driggs-Campbell, K., & Bajcsy, R. (2018). Affective Driver State Monitoring for Personalized, Adaptive ADAS. In 2018 IEEE Intelligent Transportation Systems Conference, ITSC 2018 (pp. 1017-1022). [8569585] (IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC; Vol. 2018-November). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ITSC.2018.8569585