Abstract
Traffic statistics show that compared to four-wheeled vehicles, two-wheeled vehicles have twice the rate of fatal accidents. Yet, research in Human-Machine Interface (HMI) for motorcycle riders has not progressed in comparison. This study describes and evaluates an experimental HMI collision avoidance system using a riding simulator with 15 participants in dangerous road conditions. Results showed that information from the system helped participants safely stop their vehicle due to reduced brake reaction time and deceleration. We quantified the probability of collision based on Monte-Carlo simulation and used an integrated error model to evaluate the overall reliability of the human-machine system. Final results clearly showed that the system reduced traffic accidents, despite potential malfunction.
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Lee, J., Ozaki, I., Kishino, S., Suzuki, K., Nakajima, M. (2019). Human-Machine Interface System for Motorcyclists: Quantification of Total Reliability as Human-Machine System. In: Stanton, N. (eds) Advances in Human Aspects of Transportation. AHFE 2018. Advances in Intelligent Systems and Computing, vol 786. Springer, Cham. https://doi.org/10.1007/978-3-319-93885-1_55
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DOI: https://doi.org/10.1007/978-3-319-93885-1_55
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