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Recherche d'indicateurs d'inattention en conduite automobile : apports des mesures physiologiques et comportementales

Abstract : Mind-Wandering (MW) is a particular state of inattention that everyone experience in daily tasks. It involves a change of anindividual attentional focus, from the main activity to personal thoughts. During driving, MW has many negative effectsenhancing the risk of being involved and responsible for a car accident.The objective of this thesis was to better describe the impact of MW on drivers’ physiological and behavioral variables to drawup a list of sensitive indicators to this state. MW, acting as an additional task to driving, would consume some of driver'scognitive resources. It was therefore necessary to search, by an experimental approach, an indicator of cognitive effort in driving.As the multiplicity of thoughts and their characteristics could create different levels of risk for the driver, it seemed relevant tostudy the impact of these different forms of inattention on driving.Results of various work conducted, show that heart rate change is sensitive to cognitive effort during simulated driving. A possible solution to improve this indicator and try to achieve a real-time detection of cognitive effort has been proposed to an international competition: the 2016 Valeo Innovation Challenge. Another indicator has been identified: driver's eyes appeared to be more staring during MW than during episodes of attention dedicated to driving. Lastly, analysis of electroencephalographicmeasurements revealed that MW decreases attention allocated to the different stages (sensory and cognitive) of visual information processing during simulated driving. Thus, the effect of different types of thoughts on ocular behavior, visual information processing, and on the cognitive effort indicator previously highlighted, informed about the degree of interference of different types of thoughts on the driving activity.The results of this thesis show that it seems promising to go even further in the search for indicators sensitive to MW and possibly other internal states to mitigate their negative effects on the driving activity. Gathering MW sensitive indicators, using atechnique of data fusion, could allow, in the future, the possibility to create algorithms able to supervise the driver. The gradualautomation of vehicles coupled with intelligent monitoring of drivers could limit the risk of accidents and human, societal andeconomic costs that are attributable to them.
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Submitted on : Wednesday, March 20, 2019 - 9:48:10 AM
Last modification on : Tuesday, December 8, 2020 - 10:20:37 AM
Long-term archiving on: : Friday, June 21, 2019 - 12:21:22 PM


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  • HAL Id : tel-02071126, version 1



Guillaume Pepin. Recherche d'indicateurs d'inattention en conduite automobile : apports des mesures physiologiques et comportementales. Psychologie. Université de Lyon, 2018. Français. ⟨NNT : 2018LYSE2133⟩. ⟨tel-02071126⟩



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