Publication detail

Multimodal Features for Detection of Driver Stress and Fatigue: Review

NĚMCOVÁ, A. SVOZILOVÁ, V. BUCSUHÁZY, K. SMÍŠEK, R. MÉZL, M. HESKO, B. BELÁK, M. BILÍK, M. MAXERA, P. SEITL, M. DOMINIK, T. SEMELA, M. ŠUCHA, M. KOLÁŘ, R.

Original Title

Multimodal Features for Detection of Driver Stress and Fatigue: Review

Type

journal article in Web of Science

Language

English

Original Abstract

Driver fatigue and stress significantly contribute to higher number of car accidents worldwide. Although, different detection approaches have been already commercialized and used by car producers (and third party companies), research activities in this field are still needed in order to increase the reliability of these alert systems. Also, in the context of automated driving, the driver mental state assessment will be an important part of cars in future. This paper presents state-of-the-art review of different approaches for driver fatigue and stress detection and evaluation. We describe in details various signals (biological, car and video) and derived features used for these tasks and we discuss their relevance and advantages. In order to make this review complete, we also describe different datasets, acquisition systems and experiment scenarios.

Keywords

driver fatigue; driver stress; traffic accident; physiological signals; multimodal features

Authors

NĚMCOVÁ, A.; SVOZILOVÁ, V.; BUCSUHÁZY, K.; SMÍŠEK, R.; MÉZL, M.; HESKO, B.; BELÁK, M.; BILÍK, M.; MAXERA, P.; SEITL, M.; DOMINIK, T.; SEMELA, M.; ŠUCHA, M.; KOLÁŘ, R.

Released

1. 6. 2021

Publisher

IEEE

ISBN

1558-0016

Periodical

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS

Year of study

22

Number

6

State

United States of America

Pages from

3214

Pages to

3233

Pages count

20

URL

https://ieeexplore.ieee.org/document/9031734

Full text in the Digital Library

http://hdl.handle.net/11012/195664

BibTex

@article{BUT163233,
  author="Andrea {Němcová} and Veronika {Svozilová} and Kateřina {Bucsuházy} and Radovan {Smíšek} and Martin {Mézl} and Branislav {Hesko} and Michal {Belák} and Martin {Bilík} and Pavel {Maxera} and Martin {Seitl} and Tomáš {Dominik} and Marek {Semela} and Matúš {Šucha} and Radim {Kolář}",
  title="Multimodal Features for Detection of Driver Stress and Fatigue: Review",
  journal="IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS",
  year="2021",
  volume="22",
  number="6",
  pages="3214--3233",
  doi="10.1109/TITS.2020.2977762",
  issn="1558-0016",
  url="https://ieeexplore.ieee.org/document/9031734"
}