Drowsy driver detection: Thresholds of vehicle parameters in real traffic and the new challenge of IVHS/Human factors programs - Final version - Annex : Scenarios and calculation


Type de document
Résumé / Abstract
Three factors are involved in car accidents : the road, the vehicle and the driver. The first two have recently received considerable attention. The third factor, the driver, is probably the most important. This paper deals especially with the last two factors. We are searching to develop an in-vehicle system to continuously monitor driver drowsiness (IVHS/human factors). The envisioned vehicle-based driver drowsiness detection system would continuously and unobtrusively monitor driver physiological and behavioural status in interaction with vehicle behaviour. The system may be programmed to provide an immediate warning signal when drowsiness is detected with high certainty. For this, the present study characterizes driver drowsiness states by analysing the recorded physiological, behavioural and car mechanical parameters during six hour driving periods. The aim is to compare slow EEG rhythms with the absolute fluctuation of car parameters, and to assess 'low-thresholds' of the steering wheel movements and vehicle speed. We affirm the role of EEG in the precise identification of the beginning of drowsiness in real traffic. Firstly, our paper examines the state of the art in monitoring driver states. It reviews and discusses empirical studies that assessed the relationship between EEG indices and measurements of vehicle parameters which would be employed as criteria of vigilance impairment. Secondly, it examines our experimental investigations by studying variations of car parameters during the trip versus theta and alpha rhythms. Their changes are used to define thresholds of vehicle parameters which will probably be used in the vehicle-based drowsy driver detection system in real traffic

puce  Accès à la notice sur le portail documentaire de l'IFSTTAR

  Liste complète des notices publiques de l'IFSTTAR