A Light on Physiological Sensors for Efficient Driver Drowsiness Detection System

International audienceThe significant advance in bio-sensor technologies hold promise to monitor human physiologicalsignals in real time. In the context of public safety, such technology knows notable research investigations toobjectively detect early stage of driver drowsiness that impairs driver performance under various conditions.Seeking for low-cost, compact yet reliable sensing technology that can provide a solution to drowsy stateproblem is challenging. While some enduring solutions have been available as prototypes for a while, many ofthese technologies are now in the development, validation testing, or even commercialization stages. Thecontribution of this paper is to assess current progress in the development of bio-sensors based driver drowsinessdetection technologies and study their fundamental specifications to achieve accuracy requirements. Existingmarket and research products are then ranked following the discussed specifications. The finding of this work isto provide a methodology to facilitate making the appropriate hardware choice to implement efficient yet lowcostdrowsiness detection system using existing market physiological based sensors

Driver Fatigue Detection using Mean Intensity, SVM, and SIFT

Driver fatigue is one of the major causes of accidents. This has increased the need for driver fatigue detection mechanism in the vehicles to reduce human and vehicle loss during accidents. In the proposed scheme, we capture videos from a camera mounted inside the vehicle. From the captured video, we localize the eyes using Viola-Jones algorithm. Once the eyes have been localized, they are classified as open or closed using three different techniques namely mean intensity, SVM, and SIFT. If eyes are found closed for a considerable amount of time, it indicates fatigue and consequently an alarm is generated to alert the driver. Our experiments show that SIFT outperforms both mean intensity and SVM, achieving an average accuracy of 97.45% on a dataset of five videos, each having a length of two minutes

Factors Impacting Habitable Volume Requirements: Results from the 2011 Habitable Volume Workshop

This report documents the results of the Habitable Volume Workshop held April 18-21, 2011 in Houston, TX at the Center for Advanced Space Studies-Universities Space Research Association. The workshop was convened by NASA to examine the factors that feed into understanding minimum habitable volume requirements for long duration space missions. While there have been confinement studies and analogs that have provided the basis for the guidance found in current habitability standards, determining the adequacy of the volume for future long duration exploration missions is a more complicated endeavor. It was determined that an improved understanding of the relationship between behavioral and psychosocial stressors, available habitable and net habitable volume, and interior layouts was needed to judge the adequacy of long duration habitat designs. The workshop brought together a multi-disciplinary group of experts from the medical and behavioral sciences, spaceflight, human habitability disciplines and design professionals. These subject matter experts identified the most salient design-related stressors anticipated for a long duration exploration mission. The selected stressors were based on scientific evidence, as well as personal experiences from spaceflight and analogs. They were organized into eight major categories: allocation of space; workspace; general and individual control of environment; sensory deprivation; social monotony; crew composition; physical and medical issues; and contingency readiness. Mitigation strategies for the identified stressors and their subsequent impact to habitat design were identified. Recommendations for future research to address the stressors and mitigating design impacts are presented

Monotony: the effect of task demand on subjective experience and performance

Although monotony is widely recognised as being detrimental to performance, its occurrence and effects are not yet well understood. This is despite the fact that task-related characteristics, such as monotony and low task demand, have been shown to contribute to performance decrements over time. Three empirical studies were conducted in this research to further our understanding of the factors that contribute to the experience of monotony and the role task demand may play in mitigating monotony-related effects on performance. The first study was lab-based to determine the effect of task demand on the subjective experience and performance of a computer-based monotonous task. Forty participants performed a monotonous task characterised by either low cognitive demand or high cognitive demand, as well as a number of self-report scales. Results clearly demonstrated that despite a similar subjective experience across both tasks, there were clear benefits for performance of the high demand monotonous task. Study two was designed to determine if monotony and fatigue are indeed issues for the potentially ‘at risk’ population of train drivers and if so, are there defining factors that contribute to these experiences. Survey results indicate that train drivers, particularly passenger drivers, experience monotony and fatigue on a regular basis while driving trains for work and the majority believe that these experiences adversely impact on their train management skills. Results also showed that train drivers are able to distinguish between the experiences of monotony and of fatigue and many utilise a somewhat limited range of strategies to cope with these experiences. Study three combined what was learned from the first two studies to determine if increasing the cognitive demand of a monotonous train driving task could mitigate the monotony-related effects on performance. The results clearly show that even a relatively minor increase in cognitive demand can mitigate adverse monotony-related effects on performance for extended periods of time, in this case over two hours of driving in a highly monotonous simulated scenario. Monotony is an inherent characteristic of transport industries, including rail, aviation and road transport, which can have adverse impact on safety, reliability and efficiency. These studies highlight possible strategies for mitigating these adverse effects

Un nuevo sistema para detectar la distracción y la somnolencia utilizando el tiempo de tecnología de vuelo para vehículos inteligentes

Nowadays, most countries in the world suffer several traffic issues which generate public health problems such as deaths and injuries of drivers and pedestrians. In order to reduce these fatalities, a system for automatic detection of both distraction and drowsiness is presented in this research. Artificial intelligence, computer vision and time of flight (TOF) technologies are used to compute both distraction and drowsiness indexes, in real time. Several experiments have been developed in real conditions during the day, inside a real vehicle and in laboratory conditions, to prove the efficiency of the system.La mayoría de los países en el mundo sufren de varios problemas de tráfico que generan problemas de salud pública, tales como, excesivas muertes y lesiones de los conductores y los peatones. Con el fin de reducir estas cifras de siniestralidad, en esta investigación se presenta un sistema para la detección automática de la distracción y la somnolencia. Las tecnologías de inteligencia artificial, visión por computador y una cámara de tiempo de vuelo (TOF) son utilizadas para calcular los índices de distracción y somnolencia, en tiempo real. Varios experimentos se han desarrollado en condiciones reales durante el día, dentro de un vehículo real y en el laboratorio, para probar la eficiencia del sistema

Driver Attention Assessment Using Physiological Measures from EEG, ECG, and EDA Signals †

In this paper, we consider the evaluation of the mental attention state of individuals driving in a simulated environment. We tested a pool of subjects while driving on a highway and trying to overcome various obstacles placed along the course in both manual and autonomous driving scenarios. Most systems described in the literature use cameras to evaluate features such as blink rate and gaze direction. In this study, we instead analyse the subjects' Electrodermal activity (EDA) Skin Potential Response (SPR), their Electrocardiogram (ECG), and their Electroencephalogram (EEG). From these signals we extract a number of physiological measures, including eye blink rate and beta frequency band power from EEG, heart rate from ECG, and SPR features, then investigate their capability to assess the mental state and engagement level of the test subjects. In particular, and as confirmed by statistical tests, the signals reveal that in the manual scenario the subjects experienced a more challenged mental state and paid higher attention to driving tasks compared to the autonomous scenario. A different experiment in which subjects drove in three different setups, i.e., a manual driving scenario and two autonomous driving scenarios characterized by different vehicle settings, confirmed that manual driving is more mentally demanding than autonomous driving. Therefore, we can conclude that the proposed approach is an appropriate way to monitor driver attention

Performance shaping factors affecting driver safety-related behaviour in urban rail systems : Tyne & Wear Metro case

PhD ThesisIt is accepted that train drivers’ safety performance is affected by numerous performance shaping factors (PSF). Design of the physical environment is among these factors. Even though the body of knowledge in rail human factors is increasing, it is limited as it is often i) reactive, ii) focusing mainly on single type incidents, iii) prioritising high profile accidents, iv) not always fully addressing existing risk profiles. Railway systems with different design features are usually grouped together for research purposes thus disregarding the fact that system design can alter effects of the PSFs. This is especially true for urban rail systems. A combination of concurrent and sequential research in this mixed methods thesis has investigated PSFs associated with metro systems design, using the Tyne & Wear Metro system as its application case. The PSFs embedded in everyday operations have been studied on different system levels through historic incident analysis, drivers’ surveys, semi-structured interviews, eye-tracking and simulation experiments. Some of the established methodologies have been adapted in order to address the research objectives set. Novel approaches have been developed for the deployment of in-service eye-tracking using dynamic areas of interest and the development of a low-cost high fidelity simulator using gaming software and hardware. Selected station layouts have been assessed through measures of workload, stress and signal checking behaviour thus supporting PSF inter-dependence. The results suggest the influence on the performance of arrival and departure procedures of the angle between a signal, a driver and a mirror. Among the latent conditions potentially inducing incident propagation are passenger levels, the platform side, informativeness of design elements, openness and lighting conditions of a station, and distances from a stopping position to other elements of the station design.Institute for Sustainability at Newcastle University, through the Sir James Knott and Ridley PhD Scholarshi

Novel technologies for the detection and mitigation of drowsy driving

In the human control of motor vehicles, there are situations regularly encountered wherein the vehicle operator becomes drowsy and fatigued due to the influence of long work days, long driving hours, or low amounts of sleep. Although various methods are currently proposed to detect drowsiness in the operator, they are either obtrusive, expensive, or otherwise impractical. The method of drowsy driving detection through the collection of Steering Wheel Movement (SWM) signals has become an important measure as it lends itself to accurate, effective, and cost-effective drowsiness detection. In this dissertation, novel technologies for drowsiness detection using Inertial Measurement Units (IMUs) are investigated and described. IMUs are an umbrella group of kinetic sensors (including accelerometers and gyroscopes) which transduce physical motions into data. Driving performances were recorded using IMUs as the primary sensors, and the resulting data were used by artificial intelligence algorithms, specifically Support Vector Machines (SVMs) to determine whether or not the individual was still fit to operate a motor vehicle. Results demonstrated high accuracy of the method in classifying drowsiness. It was also shown that the use of a smartphone-based approach to IMU monitoring of drowsiness will result in the initiation of feedback mechanisms upon a positive detection of drowsiness. These feedback mechanisms are intended to notify the driver of their drowsy state, and to dissuade further driving which could lead to crashes and/or fatalities. The novel methods not only demonstrated the ability to qualitatively determine a drivers drowsy state, but they were also low-cost, easy to implement, and unobtrusive to drivers. The efficacy, ease of use, and ease of access to these methods could potentially eliminate many barriers to the implementation of the technologies. Ultimately, it is hoped that these findings will help enhance traveler safety and prevent deaths and injuries to users

Peripheral vision field fatigue during simulated driving : the effects of time on task and time of day on selected psychophysiological, performance and subjective responses

Worldwide, motor accidents are responsible for a large number of deaths and disabilities (Connor et al., 2001), and one of the major causes of motor accidents is driver fatigue. Although majority of drivers are aware of the dangers of fatigued driving, accidents related to this continues to contribute to a large percentage of all accidents, between 5 and 50% (Nilsson et al., 1997; Williamson et al., 2011). The purpose of the research was to establish the effect that fatigue renders on an individual’s peripheral visual field and to determine whether a decrement in driving performance occurs at the same rate as a decrement in peripheral visual performance. Fatigue was induced through time of day as well as time on task. Sixteen students from Rhodes University were recruited, subject to no previous sleep disorders, among other criteria. Each participant was required to partake in two conditions, namely a day condition (09h00–11h00) and a night condition (23h00– 01h00). Each condition consisted of a 90 minute dual task; the primary task was a tracking task, in which participants were instructed to track a white line as accurately as possible. A secondary peripheral response task was introduced, in which participants were instructed to respond as quickly as possible to the peripheral stimuli, by pressing one of two clickers located on the steering wheel. The peripheral stimuli were located at 20º, 30º and 40º visual angle. Psychophysiological, performance and subjective measures were obtained before, during and after the main task. The pre- and post-tests included core body temperature, critical flicker fusion frequency threshold, a digit span memory test, Wits Sleepiness Scale and a NASA-TLX questionnaire. The psychophysiological and performance measures of heart rate, heart rate variability, blink frequency, blink duration, lane deviation, number of saccades towards peripheral stimuli, response time to peripheral stimuli and the percentage of missed peripheral responses were all recorded throughout the 90 minute main dual task. The results revealed significant differences (p<0.05) for heart rate variability, number of saccades towards peripheral stimuli and the Wits Sleepiness Scale, with regard to time of day. For time on task, significant effects were established for lane deviation, response time to peripheral stimuli, percentage of missed peripheral responses, heart rate, heart rate variability, blink frequency, blink duration, critical flicker fusion frequency threshold, core body temperature and the Wits Sleepiness Scale. Eccentricity was analysed and found to be significant for response time to peripheral stimuli, as well as for the percentage of missed peripheral responses; there was a significant increase in both measures with an increase in the stimuli eccentricity. No significances were established for time of day or between the pre- and post-tests conducted for the digit span memory performance; however, a significant interactional effect between the two was established. When assessing the percentage rate of decrement of driving performance compared to the percentage rate in the decrement of the missed peripheral responses, it was found that the percentage rate of decrement was equal for both measures. Thus from this research it can be seen that, concurrent with a decrement in driving performance, there are adverse effects on an individuals' peripheral vision, which have great implications for the safety of workers in industry and transport, as well as motorists. It was also established that time on task is possibly a more appropriate variable to consider than time of day, when implementing work schedules and rest breaks in industry, transport and fields alike, as more significant findings were seen for time on task compared to time of day.Adobe Acrobat 9.53 Paper Capture Plug-i