Towards cooperative management of fatigue and vigilance in railway operations - Archive ouverte HAL
Proceedings/Recueil Des Communications ITM Web of Conferences Année : 2024

Towards cooperative management of fatigue and vigilance in railway operations

Résumé

Professional drivers face fatigue and decrease of vigilance over the long driving sessions paving their everyday life. This naturally occurring phenomenon is acknowledged and preventive measures, adapted to the vehicles and missions, are deployed around the world to limit the related risks. As technology opened the way to affordable probing of human biosignals and activities, more active strategies are investigated such as sleepiness monitoring and alert systems. Such systems already existed in trains, although in a more primitive form, known as "dead-man switch". As the limitations of this system in detecting actual vigilance decrements is known from practitioners, we took upon ourselves to explore the opportunities offered by the recent developments, under the strict security constraint that characterises railway operations. Going further than monitoring and alert, we consider the ideas of a bio-signal feedback loop and adaptive levels of automation to encourage a real cooperation between the driver and the system in managing fatigue and vigilance. This challenge is particularly significant in teleoperation, which emerges as a potential evolution of the railway activity where fatigue and vigilance are affected by information loss and increased reliance on visual information. Such cooperative work would pave the way for a new definition of what a train driver is, emphasizing its critical role of safeguarding the train and its passengers. This is especially important in a context of autonomous systems' proliferation, putting the drivers' position at risks.
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hal-04814184 , version 1 (02-12-2024)

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Quentin Berdal, Quentin Gadmer, Philippe Richard. Towards cooperative management of fatigue and vigilance in railway operations. International Conference on Mobility, Artificial Intelligence and Health (MAIH2024), ITM Web of Conferences, 69, pp.03006, 2024, ⟨10.1051/itmconf/20246903006⟩. ⟨hal-04814184v1⟩

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