Search results for: drowsiness
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2

Search results for: drowsiness

2 Comparative Study of Fatigue and Drowsiness in the Night-time Passenger Transportation Industry in Japan

Authors: Hiroshi Ikeda

Abstract:

In this research, a questionnaire survey was conducted to measure nap, drowsiness and fatigue of drivers who work for long shifts, to discuss about the work environment and health conditions for taxi and bus drivers who work at night-time. The questionnaire sheet used for this research was organized into the following categories: tension/tiredness, drowsiness while driving, and the nap situation during night-time work. The number of taxi drivers was 127 and the number of bus drivers was 40. Concerning the results of a comparison of nap hours of taxi and bus drivers, the taxi drivers’ nap hours are overwhelmingly shorter, and also the frequency of drivers who experience drowsiness is higher. The burden on bus drivers does not change because of the system of a two-driver rotation shift. In particular, the working environment of the taxi driver may lead to greater fatigue accumulation than the bus driver’s environment.

Keywords: Bus and taxi, drowsiness, fatigue, nap.

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1 Drowsiness Warning System Using Artificial Intelligence

Authors: Nidhi Sharma, V. K. Banga

Abstract:

Nowadays, driving support systems, such as car navigation systems, are getting common, and they support drivers in several aspects. It is important for driving support systems to detect status of driver's consciousness. Particularly, detecting driver's drowsiness could prevent drivers from collisions caused by drowsy driving. In this paper, we discuss the various artificial detection methods for detecting driver's drowsiness processing technique. This system is based on facial images analysis for warning the driver of drowsiness or in attention to prevent traffic accidents.

Keywords: Neuro-Fuzzy Model, Halstead Model, Walston-FelixModel, Bailey-Basili Model, Doty Model, GA Based Model, GeneticAlgorithm.

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