Abstract
For trains, cars and other vehicles, the quality of the user comfort level is affected significantly by the driver skill level such as agility, experience and physical condition. In order to assist the drivers, in this paper, we propose a brake assist function for railway vehicles using Fuzzy Logic. We present a comparison study for different Fuzzy Inference types (models). The proposed function provides an intelligent breaking for the train drivers considering velocity, current brake level and environment status on the railway. We evaluate four Fuzzy inference types. The simulation results show that Type-2 FLC2 can provide better brake assisting function for train drivers than other models.
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Tsuneyoshi, M., Ikeda, M., Barolli, L. (2023). A Brake Assisting Function for Railway Vehicles Using Fuzzy Logic: A Comparison Study for Different Fuzzy Inference Types. In: Barolli, L. (eds) Advances on Broad-Band Wireless Computing, Communication and Applications. BWCCA 2022. Lecture Notes in Networks and Systems, vol 570. Springer, Cham. https://doi.org/10.1007/978-3-031-20029-8_29
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