Effects of Time of Day and Sleep Deprivation on Motorcycle-Driving Performance

The aim of this study was to investigate whether motorcycle handling capabilities – measured by means of the efficiency of emergency manoeuvres – were dependent on prior sleep deprivation and time of day. Twelve male participants voluntarily took part in four test sessions, starting at 6 a.m., 10 a.m., 2 p.m., and 6 p.m., following a night either with or without sleep. Each test session comprised temperature and sleepiness measurements, before three different types of motorcycling tests were initiated: (1) stability in straight ahead riding at low speed (in “slow motion” mode and in “brakes and clutch” mode), (2) emergency braking and (3) crash avoidance tasks performed at 20 kph and 40 kph. The results indicate that motorcycle control at low speed depends on time of day, with an improvement in performance throughout the day. Emergency braking performance is affected at both speeds by time of day, with poorer performance (longer total stopping distance, reaction time and braking distance) in the morning, and also by sleep deprivation, from measurements obtained at 40 kph (incorrect initial speed). Except for a tendency observed after the sleepless night to deviate from the initial speed, it seems that crash avoidance capabilities are quite unaffected by the two disturbance factors. Consequently, some motorcycle handling capabilities (stability at low speed and emergency braking) change in the same way as the diurnal fluctuation observed in body temperature and sleepiness, whereas for others (crash avoidance) the participants were able to maintain their initial performance level despite the high levels of sleepiness recorded after a sleepless night. Motorcycle riders have to be aware that their handling capabilities are limited in the early morning and/or after sleep deprivation. Both these situations can increase the risk of falls and of being involved in a road accident

Comportement des conducteurs de deux roues motorisés (influences de l heure de la journée et de la privation de sommeil sur les performances de conduite réelle et simulée)

Ce travail vise à améliorer les connaissances relatives aux effets de l heure de la journée et de la privation de sommeil sur les performances de conduite d un deux-roues motorisé, et sur différentes ressources cognitives et/ou physiques qui y contribuent. Pour répondre à cet objectif, six études ont été menées. En se basant sur différents niveaux d analyse, grâce à l utilisation d outils de mesure innovants (véhicule instrumenté, simulateur de conduite), ces études ont permis de montrer qu il existe, à l instar de la conduite automobile, une fluctuation diurne des performances de conduite d un deux-roues motorisé. Ces performances, comme l ensemble des ressources qui y contribuent, s améliorent au cours de la journée, en passant par des niveaux faibles le matin (06:00 h) et maximaux en fin d après-midi (18:00 h). L utilisation de contre-mesures, telles qu un réveil 1 ou 2 h avant la conduite et/ou une prise alimentaire légère ne suffit pas à compenser la dégradation des performances, observée le matin. Cette fluctuation diurne des performances persiste le lendemain d une privation totale de sommeil, selon une amplitude réduite. Au cours de tests de conduite de courte durée, les conducteurs semblent mettre en place des mécanismes de compensation entre leurs différentes ressources, affectées à un niveau variable, afin de maintenir un niveau de performance globale de conduite satisfaisant. Cependant, au-delà de 30 h d éveil, et lorsque le niveau de complexité de la situation de conduite augmente, les effets délétères du manque de sommeil sont accentués. Ces études possèdent un impact direct en termes de sécurité routière, et confirment la nécessité de faire prendre conscience des dangers que possède la conduite en état d hypovigilance.The aim of this work consists in improving knowledge concerning the cognitive and physical resources underlying motorcycle riding as well as riding performance itself. More specifically, we studied time-of-day and sleep deprivation effects of on these components. To reach this goal, six studies have been done. Innovating tools such as an instrumented vehicle and a riding simulator have been used as well as different levels of analysis. Taken together, these studies revealed a daily fluctuation of motorcycle riding performances, as it had been shown earlier for car driving. Motorcycle riding performance, as well as its underlying resources, increases during the day, from a low level at 06:00 h to a high level at 18:00 h. It is still the case when wake-up occurred 1 or 2 hours before driving and/or when participants had a light breakfast. Furthermore, this daily fluctuation of riding performances still appears after total sleep deprivation. However, the amplitude of this fluctuation decreases. During short term riding tests, riders appear to proceed to compensations between their different resources, in the sense that they regulate the level of activation of each resource to keep the global riding performance to an acceptable level. However, over 30 h of sleeplessness, especially when the task complexity increases, the negative effects of sleep deprivation are increased. In conclusion, these studies have a direct impact in regards to road safety and confirm the necessity to take into account the dangers of riding in a state of reduced vigilance.CAEN-BU Sciences et STAPS (141182103) / SudocSudocFranceF

The effects of sleep deprivation and time of day on cognitive performance

The extent to which the diurnal fluctuations of different cognitive processes could be affected by sleep loss may be explored to predict performance decrements observed in the real world. Twenty healthy male subjects voluntarily took part in 8 test sessions at 06:00, 10:00, 14:00, and 18:00 h, following either a night with or without sleep in random order. Measurements included oral temperature, simple reaction time, sign cancelation, Go/NoGo, and the Purdue pegboard test. The results indicate that simple reaction time and motor coordination had morning-afternoon variations closely following the rhythms of temperature and vigilance. Inhibitory attention (Go/NoGo) presented no morning-afternoon variations. Sleep deprivation may affect the profiles of cognitive performance depending on the processes solicited. Sustained and inhibitory attention are particularly affected in the morning (after 24 and 28 waking hours), while a complex task (visuo-motor coordination) would be affected after 32 waking hours only

Car sickness in real driving conditions: Effect of lateral acceleration and predictability reflected by physiological changes

International audienceWith the development of autonomous vehicles, car sickness may affect increasing numbers of car occupants. Car manufacturers have a real need to understand the causes of these symptoms, which occur mainly when car occupants are not engaged in a driving task. This study is the first to evaluate, in real driving conditions, the impact of lateral acceleration level and vehicle path predictability on car sickness incidence and severity, and the potential relationship with physiological changes. 24 healthy volunteers participated as front seat passengers in a slalom session inducing lateral movements at very low frequency (0.2 Hz). They were continuously monitored via physiological recordings and provided subjective car sickness ratings (CSR) after each slalom, using a 5-point likert scale. CSR reveal that (i) the greater the lateral acceleration and (ii) the less predictable the vehicle path, the more severe the car sickness symptoms in real driving conditions. An increase in several physiological parameters is also found simultaneously with higher CSR, demonstrating activation of the sympathetic nervous system. Moreover, the linear regression applied to our data suggests that these physiological parameters can be used to indicate car sickness severity. Moreover, the linear regression applied to our data suggests that the evolution of these physiological parameters may reflect the CSR level indicated by participants

Monitoring driver drowsiness in partially automated vehicles: Added value from combining postural and physiological indicators

International audienceDrowsiness at the wheel is one of the leading causes of road fatalities. Driver monitoring systems (DMS) mainly rely on vehicle-based data and drivers' facial information to detect drowsiness. However, the introduction of partially autonomous driving will change the way we drive, letting the vehicle manage the driving task while drivers may be free to engage in non-driving tasks. This calls for new ways of detecting drowsiness, and even sleeping, at the wheel. Here, 22 participants drove for 100 min in a static simulator under level-2 automation on a 2 × 2 motorway. Postural (i. e., pressure and movements) and physiological (i.e., cardiac and respiratory) indicators were continuously recorded, while PERCLOS70 was used to classify drowsiness. The results reveal different physiological and postural signatures for the different states of drowsiness defined. While slight drowsiness is mainly associated with a higher heart rate, slower breathing, and an increased number of movements on the seat, being asleep is characterized by a lower heart rate and a slouched position on the seat. This study points to the relevance of using postural indicators in combination with physiological data to detect driver drowsiness. Focusing on the partially automated vehicle, it explores not only resistance to drowsiness but also sleeping at the wheel

Les automobilistes confrontés à des événements dangereux dans des situations réelles par rapport à des situations simulées : Aspects déclaratifs, comportementaux et physiologiques pour évaluer le sentiment de présence des conducteurs

International audienceMore than 1.3 million people lose their lives every year in traffic accidents. Improving road safety requires designing better vehicles and investigating drivers' abilities more closely. Driving simulators are constantly being used for this purpose, but the question which often arises as to their validity tends to be a barrier to developments in this field. Here we studied the validity of a simulator, defined as how closely users' behavior under simulated conditions resembles their behavior on the road, based on the concept of drivers' feeling of presence. For this purpose, the driving behavior, physiological state and declarative data of 41 drivers were tested in the Sherpa2 simulator and in a real vehicle on a track while driving at a constant speed. During each trial, drivers had to cope with an unexpected hazardous event (a one-meter diameter gym ball crossing the road right in front of the vehicle), which occurred twice. During the speed-maintenance task, the simulator showed absolute validity, in terms of the driving and physiological parameters recorded. During the first hazardous event, the physiological parameters showed that the level of arousal (Low Heart Rate/High Heart Rate ratio x10) increased up to the end of the drive. On the other hand, the drivers' behavioral (braking) responses were 20% more frequent in the simulator than in the real vehicle, and the physiological state parameters showed that stress reactions occurred only in the real vehicle (+5 beats per minute, +2 breaths per minute and the phasic skin conductance increased by 2). In the subjects' declarative data, several feeling of presence sub-scales were lower under simulated conditions. These results suggest that the validity of motion based simulators for testing drivers coping with hazards needs to be questioned

Effects of Waking Time and Breakfast Intake Prior to Evaluation of Psychomotor Performance in the Early Morning

Many studies conducted in the field of chronobiology report diurnal fluctuation incognitive and physical performance that occurs in phase with the body temperaturecircadian rhythm. Waking time and whether or not breakfast is consumed arecurrently considered to influence the diurnal fluctuation in data collected in themorning at 06:00 h and evening at 18:00 h. Nineteen male subjects participated infour test sessions to examine if wake-up time (04:00 h or 05:00 h) and eating or not eating breakfast influence psychomotor performance capacity at 06:00 h. All four sessions were separated by 36 h and were completed in a counterbalanced order. Each test session comprised sign cancellation, Epworth Sleepiness Scale, simple reaction time, and manual dexterity tests. Most of the results indicate that psychomotor performance when evaluated at 06:00 h under each of the four different study situations (two waking times and two breakfast conditions) is not statistically significantly different. Consequently, previous results that documented diurnal fluctuations in morning and evening performance capacities, with test sessions at 06:00 h, are confirmed. Being less efficient in the early morning than in the afternoon potentially exposes people to elevated risk of accident and injury at this time of the day. Prior waking time and/or consumption of a light meal, plus other countermeasures mentioned in the literature, are insufficient to prevent this risk

Food restriction alters salivary cortisol and α-amylase responses to a simulated weightlifting competition without significant performance modification

Food restriction alters salivary cortisol and α-amylase responses to a simulated weightlifting competition without significant performance modificatio

Adapting artificial neural networks to a specific driver enhances detection and prediction of drowsiness

International audienceMonitoring car drivers for drowsiness is crucial but challenging. The high inter-individual variability observed in measurements raises questions about the accuracy of the drowsiness detection process. In this study, we sought to enhance the performance of machine learning models (Artificial Neural Networks: ANNs) by training a model with a group of drivers and then adapting it to a new individual. Twenty-one participants drove a car simulator for 110 min in a monotonous environment. We measured physiological and behavioral indicators and recorded driving behavior. These measurements, in addition to driving time and personal information, served as the ANN inputs. Two ANN-based models were used, one to detect the level of drowsiness every minute, and the other to predict, every minute, how long it would take the driver to reach a specific drowsiness level (moderately drowsy). The ANNs were trained with 20 participants and subsequently adapted using the earliest part of the data recorded from a 21st participant. Then the adapted ANNs were tested with the remaining data from this 21st participant. The same procedure was run for all 21 participants. Varying amounts of data were used to adapt the ANNs, from 1 to 30 min, Model performance was enhanced for each participant. The overall drowsiness monitoring performance of the models was enhanced by roughly 40% for prediction and 80% for detection

Drivers’ performances and their subjective feelings about their driving during a 40-min test on a circuit versus a dynamic simulator

International audienceCar manufacturers expect driving simulators to be reliable research and development tools. Questions arise, however, as to whether drivers’ behavior on simulators exactly matches that observed when they are driving real cars. Drivers’ performances and their subjective feelings about their driving were compared between two groups during a 40-min driving test on the same circuit in a real car (n = 20) and a high-fidelity dynamic simulator (n = 27). Their speed and its variability, the braking force and the engine revolutions per minute (rpm) were recorded five times on a straight line and three times on a curve. The differences observed in these measurements between circuit driving (CD) and simulator driving (SD) from the 6th to 40th minute showed no significant changes during the drive. The drivers also completed the NASA Raw Task Load Index (NASA RTLX) questionnaire and the Simulator Sickness Questionnaire (SSQ) and estimated the ease and standard of their own driving performances. These subjective feelings differed significantly between the two groups throughout the experiment. The SD group’s scores on the NASA RTLX and SSQ questionnaires increased with time and the CD group’s perceived driving quality and ease increased with time, reaching non-significantly different levels from their usual car driving standards by the end of the drive. These findings show the existence of a fairly good match between real-life and simulated driving, which stabilized six minutes after the start of the test, regardless of whether the road was straight or curved. These objective findings and subjective assessments suggest possible ways of improving the match between drivers’ performances on simulators and their real-life driving behavior