Use this URL to cite or link to this record in EThOS:
Title: Chromatic driver fatigue monitoring system
Author: Ker Keong, Alex Koh
ISNI:       0000 0001 3597 4954
Awarding Body: University of Liverpool
Current Institution: University of Liverpool
Date of Award: 2008
Availability of Full Text:
Access from EThOS:
Sleep related vehicle accidents have been under publicised but remains as one of the main causes of road traffic accidents, as much as drink driving. This research aims to reduce this worldwide problem by developing a system to monitor fatigue driving. The thesis describes the research into the application of chromatic data processing techniques to detect early physiological and physical indicators of fatigue. Physiological factors that influence drivers are based on the duration of the drive, how much rest they have throughout the journey and the quality of sleep they had prior to the drive. The physiological indicator algorithm of the system is developed to take account of these factors and calculates the tiredness level. The chromatic technique is then used to analyse the results to establish trends and signatures of early fatigue situations where a warning system can be introduced. The chromatic signatures of fatigue have been established using results from 20 road tests conducted by professional drivers. Physical indicators such as early drowsy driving are detected by monitoring the behaviour of the vehicle. Micro sleep (e.g. head nodding, slow eye-blinking) can lead to lane drifting and vehicle swerving. These events are being regarded as early physical signs of sleepy driving. The main sensor for detecting the lateral yaw motion of the vehicle is a miniaturised gyroscope. Chromatic analysis is applied to the gyroscope output to identify and differentiate fatigue related events (e.g. swerves and lane drifting) from normal driving (e.g. left and right turning, roundabouts and bumpy roads) Combining the extracted information of the physiological and physical indicators, a Chromatic Fatigue Driving System can be developed as a tail safe system which monitors and alerts driver during critical fatigue conditions.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available