Citation

Jan MT, Hashemi A, Jang J, Yang K, Zhai J, Newman D, Tappen R, Furht B. Lect. Notes Netw. Syst. 2023; 560(V2): 776-796.

Copyright

(Copyright © 2023, Holtzbrinck Springer Nature Publishing Group)

DOI

10.1007/978-3-031-18458-1_53

PMID

36972186

PMCID

PMC10037317

Abstract

Proceedings of the Future Technologies Conference (FTC) 2022. Volume 2. Future Technologies Conference (7th : 2022 : Vancouver, B.C.; Online)

Drowsy drivers cause the most car accidents thus, adopting an efficient drowsiness detection system can alert the driver promptly and precisely which will reduce the numbers of accidents and also save a lot of money. This paper discusses many tactics and methods for drowsy driving warning. The non-intrusive nature of most of the strategies mentioned and contrasted means both vehicular and behavioural techniques are examined here. Thus, the latest strategies are studied and discussed for both groups, together with their benefits and drawbacks. The goal of this review was to identify a practical and low-cost approach for analysing elder drivers' behaviour.

Language: en

Keywords

Fatigue; Drowsiness; behavioural based; early-stage dementia; Vehicular based