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A significant number of road accidents are caused by impaired driver attention, such as inattention and more specifically mind wandering. Accordingly, to enhance drivers’ safety, one solution proposed to avoid accidents due to mind wandering is to automate vehicle driving. However, vehicles on the market are not yet fully autonomous, and the driver retains supervisory status and must be able to regain control of the vehicle when asked to do so. This passive supervision can lead to under-activation of the attentional system and mind wandering, hindering the driver's ability to regain control of the vehicle if requested. To address this societal issue, the physiological indicators of mind wandering were investigated in delegated driving. Forty-three participants took part in this experiment. They were seated in a car simulator, and supervised a simulated autonomous driving environment for 20 min. Every 60 to 120 s, they were asked to declare whether their attention was focused on the supervisory task or not. Thus, it permits distinguishing between two attentional situations: being focused on the task or wandering thoughts. There were 11 questionnaires and their order reflected the temporal progression throughout the experiment. Before each declaration, cardiac and electrodermal activities were measured. The Linear Mixed Model analysis showed that the attentional situation was a predictor of the number of phasic skin conductance responses and time was a predictor of the tonic skin conductance level. Individuals had fewer phasic responses when they were in mind wandering state than when they were focused on the task and the tonic level varied over time. The attentional situation, the time, and their interaction were predictors of SDNN reactivity (Standard Deviation of Normal-to-Normal intervals). SDNN varied over time and reactivity was lower in mind wandering. The results from the other cardiac indicators were not significant. These results showed specific cardiac and electrodermal signatures of mind wandering. They are discussed as a consequence of low engagement in the task when drivers are mind wandering. Considering these indicators could enable the detection of mind wandering in autonomous driving before a takeover request.

Research works on operator monitoring underline the benefit of taking into consideration several signal modalities to improve accuracy for an objective mental state diagnosis. Heart rate (HR) is one of the most utilized systemic measures to assess cognitive workload (CW), whereas, respiration parameters are hardly utilized. This study aims at verifying the contribution of analyzing respiratory signals to extract features to evaluate driver's activity and CW variations in driving. Eighteen subjects participated in the study. The participants carried out two different cognitive tasks requiring different CW demands, a single task as well as a competing cognitive task realized while driving in a simulator. Our results confirm that both HR and breathing rate (BR) increase in driving and are sensitive to CW. However, HR and BR are differently modulated by the CW variations in driving. Specifically, HR is affected by both driving activity and CW, whereas, BR is suitable to evidence a variation of CW only when driving is not required. On the other hand, spectral features characterizing respiratory signal could be also used similarly to HR variability indices to detect high CW episodes. These results hint the use of respiration as an alternative to HR to monitor the driver mental state in autonomic vehicles in order to predict the available cognitive resources if the user has to take over the vehicle.

Partially autonomous vehicles can help minimize human errors. However, being free from some driving subtasks can result in a low vigilance state, which can affect the driver’s attention towards the road. The present study first tested whether drivers of partially autonomous vehicles would benefit from the addition of auditory versions of the messages presented in variable message signs (VMS), particularly, when they find themselves in a monotonous driving situation. A second aim was to test whether the addition of auditory messages would also produce an indirect effect on the driver’s vigilance, improving performance on other driving subtasks not related to the message processing. Forty-three volunteers participated in a driving simulator study. They completed two tasks: (a) a VMS task, where they had to regain manual control of the car if the VMS message was critical, and (b) a car-following task, where they had to pay attention to the preceding car to respond to occasional brake events. Behavioral and EEG data were registered. Overall, results indicated that the addition of audio messages helped drivers process VMS information more effectively and maintain a higher level of vigilance throughout the driving time. These findings would provide useful information for the development of partially automated vehicles, as their design must guarantee that the driver remains attentive enough to assume control when necessary.

This study aimed at investigating how driver’s mental workload could be assessed during driving, using driving performance as well as electrophysiological and subjective data. Participants had to follow a lead vehicle at a safe and constant distance and to deal with two particular driving events (overtaking and pedestrian occurrence) within two sessions (baseline and experimental) on a driving simulator. Traffic density and time pressure (overtaking event) and time pressure (pedestrian event) were increased in the experimental session in order to induce a higher workload. Participants filled NASA TLX questionnaire after each driving session. Electrophysiological parameters (SCL, ECG), driving performance (SDLP and response to speed change of the lead vehicle: coherence, delay and gain) were analysed after each event in two temporal windows (30 s and 5 min). Results showed that both performance and physiological variables differed as a function of traffic conditions and time pressure. Moreover, while performance variations were systematically observed over a long period (5 min after the events), effects on mean SCL data obtained from experimental session notably differed from baseline values within 30 s after the events. Results are discussed in term of mental workload and suggestions are made about the safety systems that could monitor driver’s mental state.

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Research works on operator monitoring underline the benefit of taking into consideration several signal modalities to improve accuracy for an objective mental state diagnosis. Heart rate (HR) is one of the most utilized systemic measures to assess cognitive workload (CW), whereas, respiration parameters are hardly utilized. This study aims at verifying the contribution of analyzing respiratory signals to extract features to evaluate driver's activity and CW variations in driving. Eighteen subjects participated in the study. The participants carried out two different cognitive tasks requiring different CW demands, a single task as well as a competing cognitive task realized while driving in a simulator. Our results confirm that both HR and breathing rate (BR) increase in driving and are sensitive to CW. However, HR and BR are differently modulated by the CW variations in driving. Specifically, HR is affected by both driving activity and CW, whereas, BR is suitable to evidence a variation of CW only when driving is not required. On the other hand, spectral features characterizing respiratory signal could be also used similarly to HR variability indices to detect high CW episodes. These results hint the use of respiration as an alternative to HR to monitor the driver mental state in autonomic vehicles in order to predict the available cognitive resources if the user has to take over the vehicle.

En 2013, on estime que 40 à 50% des accidents corporels seraient dus à un défaut d’attention de la part du conducteur. Des travaux récents ont mis en évidence la possibilité de détecter des états attentionnels dégradés afin de pouvoir mieux assister le conducteur; ce thème de recherche pourrait ouvrir la voie à de nouvelles perspectives en sécurité routière. Cette étude se concentre sur la détection de l’effort cognitif fourni par les conducteurs et cherche, par l’analyse de la variation du rythme cardiaque, à identifier un indicateur d’effort sensible sur de courtes fenêtres temporelles. Dix-huit conducteurs ont participé à l’étude. Ils ont été répartis dans 8 conditions expérimentales dans lesquelles ils devaient effectuer une tâche cognitive de manière passive (simple écoute) ou active (comptage) lors d’une session de conduite ou non. Le comptage présentait 2 niveaux de difficultés (comptage de bips vs addition de nombre à partir d’une tâche visuo-spatiale). Les rythmes cardiaques et leurs variations ont été collectés durant toutes les sessions. Au terme de notre étude, il s’avère qu’il est possible de distinguer des patterns cardiaques d’effort et de relaxation sur de courtes fenêtres temporelles en moyennant la variation du rythme cardiaque sur un nombre conséquent d’épisodes. L’indicateur d’effort cognitif, caractérisé par deux composantes cardiaques (ECR1 et ECR2) et identifié par plusieurs auteurs comme sensible dans des tâches de laboratoire, s’est montré aussi sensible en conduite automobile. En effet, dans les secondes qui suivent un effort cognitif, une légère décélération du rythme cardiaque puis une forte accélération ont été mises en évidence. A l’inverse, sans effort cognitif, une simple décélération cardiaque a été observée. Les résultats obtenus ont permis de montrer des accélérations cardiaques plus importantes lors d’une double tâche (comparée à une tâche simple) et lors d’une tâche cognitive difficile (comparée à une tâche cognitive facile). Ces résultats laissent supposer qu’un indicateur quantitatif de l’effort cognitif pourrait être approché par l’étude de la variation du rythme cardiaque en conduite automobile. Dans l’objectif de développer des systèmes capables de détecter en temps réel un effort cognitif important, les dispositifs devront être capables de visualiser l’effort sur un unique évènement. Explorer la faisabilité de la suppression de l’influence de la respiration sur le rythme cardiaque pourrait améliorer la sensibilité de l’indicateur en question. Si cela s’avère réalisable et si la correction effectuée permet de mieux détecter l’effort cognitif en temps réel, des assistances adaptatives pourraient alors alerter le conducteur ou pallier ses erreurs lorsque celui-ci ne peut plus assurer la tâche de conduite en raison d’un effort cognitif important. In 2013, attention deficits accounted for 40 to 50% of injury accidents. Recent studies have succeeded in detecting impaired states of attention, with a view to assisting the driver, and provide a new opportunity to increase road safety. This study focuses on the detection of drivers’ cognitive effort and seeks, through the study of heart rate change (HRC), to identify a sensitive indicator of cognitive effort in short time windows. Eighteen young drivers participated in the study and took part in 8 experimental sessions where they performed a passive or active cognitive task (counting) while driving or not. The counting task had two difficulty levels (counting of beeps vs visuospatial skills and number adding). Participants’ heart rates were monitored during all tasks. Previous results recorded in laboratory conditions have been replicated during driving: during the first seconds after a cognitive effort, there is a slight deceleration and a sharp acceleration in heart rate. Conversely, in the absence of cognitive effort, simple cardiac deceleration was observed. Our study confirms that it is possible to distinguish HRC in response to a cognitive effort over short time windows by observing the grand mean of evoked cardiac responses at 0.5s intervals from stimulus onset when averaged over a significant number of episodes. The new opportunities offered with this cognitive effort indicator are discussed. Recent literature data show that the removal of respiratory influence from heart rate is feasible. With such correction, it seems possible to improve the sensitivity of HRC, and HR acceleration should be observed without averaging the HRC over many trials. If this proves effective, using an algorithm to detect cognitive effort in real time, future assistance devices could warn drivers or overcome their mistakes when they no longer control driving activity because of a cognitive effort.

The mismatch negativity (MMN) component of auditory event-related brain potentials can be used as a probe to study the representation of sounds in auditory sensory memory (ASM). Yet it has been shown that an auditory MMN can also be elicited by an illusory auditory deviance induced by visual changes. This suggests that some visual information may be encoded in ASM and is accessible to the auditory MMN process. It is not known, however, whether visual information affects ASM representation for any audiovisual event or whether this phenomenon is limited to specific domains in which strong audiovisual illusions occur. To highlight this issue, we have compared the topographies of MMNs elicited by non-speech audiovisual stimuli deviating from audiovisual standards on the visual, the auditory, or both dimensions. Contrary to what occurs with audiovisual illusions, each unimodal deviant elicited sensory-specific MMNs, and the MMN to audiovisual deviants included both sensory components. The visual MMN was, however, different from a genuine visual MMN obtained in a visual-only control oddball paradigm, suggesting that auditory and visual information interacts before the MMN process occurs. Furthermore, the MMN to audiovisual deviants was significantly different from the sum of the two sensory-specific MMNs, showing that the processes of visual and auditory change detection are not completely independent.

En 2013, on estime que 40 à 50 % des accidents corporels seraient dus à un défaut d’attention de la part du conducteur. Des travaux récents ont mis en évidence la possibilité de détecter des états attentionnels dégradés afin de pouvoir mieux assister le conducteur ; ce thème de recherche pourrait ouvrir la voie à de nouvelles perspectives en sécurité routière. Cette étude se concentre sur la détection de l’effort cognitif fourni par les conducteurs et cherche, par l’analyse de la variation du rythme cardiaque, à identifier un indicateur d’effort sensible sur de courtes fenêtres temporelles. Dix-huit conducteurs ont participé à l’étude. Ils ont été répartis dans 8 conditions expérimentales dans lesquelles ils devaient effectuer une tâche cognitive de manière passive (simple écoute) ou active (comptage) lors d’une session de conduite ou non. Le comptage présentait 2 niveaux de difficultés (comptage de bips vs addition de nombre à partir d’une tâche visuo-spatiale). Les rythmes cardiaques et leurs variations ont été collectés durant toutes les sessions. Au terme de notre étude, il s’avère qu’il est possible de distinguer des patterns cardiaques d’effort et de relaxation sur de courtes fenêtres temporelles en moyennant la variation du rythme cardiaque sur un nombre conséquent d’épisodes. L’indicateur d’effort cognitif, caractérisé par deux composantes cardiaques (ECR1 et ECR2) et identifié par plusieurs auteurs comme sensible dans des tâches de laboratoire, s’est montré aussi sensible en conduite automobile. En effet, dans les secondes qui suivent un effort cognitif, une légère décélération du rythme cardiaque puis une forte accélération ont été mises en évidence. A l’inverse, sans effort cognitif, une simple décélération cardiaque a été observée. Les résultats obtenus ont permis de montrer des accélérations cardiaques plus importantes lors d’une double tâche (comparée à une tâche simple) et lors d’une tâche cognitive difficile (comparée à une tâche cognitive facile). Ces résultats laissent supposer qu’un indicateur quantitatif de l’effort cognitif pourrait être approché par l’étude de la variation du rythme cardiaque en conduite automobile. Dans l’objectif de développer des systèmes capables de détecter en temps réel un effort cognitif important, les dispositifs devront être capables de visualiser l’effort sur un unique évènement. Explorer la faisabilité de la suppression de l’influence de la respiration sur le rythme cardiaque pourrait améliorer la sensibilité de l’indicateur en question. Si cela s’avère réalisable et si la correction effectuée permet de mieux détecter l’effort cognitif en temps réel, des assistances adaptatives pourraient alors alerter le conducteur ou pallier ses erreurs lorsque celui-ci ne peut plus assurer la tâche de conduite en raison d’un effort cognitif important. In 2013, attention deficits accounted for 40 to 50 % of injury accidents. Recent studies have succeeded in detecting impaired states of attention, with a view to assisting the driver, and provide a new opportunity to increase road safety. This study focuses on the detection of drivers’ cognitive effort and seeks, through the study of heart rate change (HRC), to identify a sensitive indicator of cognitive effort in short time windows. Eighteen young drivers participated in the study and took part in 8 experimental sessions where they performed a passive or active cognitive task (counting) while driving or not. The counting task had two difficulty levels (counting of beeps vs visuospatial skills and number adding). Participants’ heart rates were monitored during all tasks. Previous results recorded in laboratory conditions have been replicated during driving: during the first seconds after a cognitive effort, there is a slight deceleration and a sharp acceleration in heart rate. Conversely, in the absence of cognitive effort, simple cardiac deceleration was observed. Our study confirms that it is possible to distinguish HRC in response to a cognitive effort over short time windows by observing the grand mean of evoked cardiac responses at 0.5 s intervals from stimulus onset when averaged over a significant number of episodes. The new opportunities offered with this cognitive effort indicator are discussed. Recent literature data show that the removal of respiratory influence from heart rate is feasible. With such correction, it seems possible to improve the sensitivity of HRC, and HR acceleration should be observed without averaging the HRC over many trials. If this proves effective, using an algorithm to detect cognitive effort in real time, future assistance devices could warn drivers or overcome their mistakes when they no longer control driving activity because of a cognitive effort.