Event-Related Potential Responses of Motorcyclists Towards Rear End Collision Warning System

Abstract : There are many types of collision warning systems to increase the safety of motorcyclists. These systems use different types of collision detection techniques with each one having some limitations, restricting the performance of the system. To find the effectiveness of collision warning system notifications, it is important to study the physiological response of drivers toward these systems. Existing studies are limited to the physiological response of car drivers and use only buzzer warnings for these systems. Unfortunately, no such work in that particular domain has been reported for motorcyclists. Since motorcycles have different maneuverability as compared with cars and other vehicles, it is important to investigate the response of motorcyclists toward these collision warning systems. Also, it is believed that providing verbal information about any potential hazard will further assist the motorcyclist to avoid it. The aim of this paper is to investigate the physiological responses of motorcyclists to the rear end collision warning system when auditory verbal warnings are utilized. To study the response of the motorcyclists, the N100, N200, P300, and N400 eventrelated potential components have been extracted from the recorded Electroencephalography data. It has been found that the rear end collision warning system with auditory verbal warnings significantly increases the alertness of the motorcyclist and can be helpful to avoid the possible rear-end collision scenarios. This system has shown positive effects at neural levels on motorcyclists and reduces their reaction time and attentional resources required for processing the target correctly.
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Soumis le : lundi 27 août 2018 - 16:21:11
Dernière modification le : mercredi 17 juillet 2019 - 10:24:03

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Muhammad Muzammel, Mohd Zuki Yusoff, Fabrice Meriaudeau. Event-Related Potential Responses of Motorcyclists Towards Rear End Collision Warning System. IEEE Access, IEEE, 2018, 6, pp.31609 - 31620. ⟨https://ieeexplore.ieee.org/document/8401685/authors⟩. ⟨10.1109/ACCESS.2018.2845899⟩. ⟨hal-01862733⟩

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