Abstract
In this paper, we propose and implement an intelligent system based on Fuzzy Logic (FL) for determining the driver’s stress in Vehicular Ad hoc Networks (VANETs) considering driver’s impatience, the behavior of other drivers, and the traffic condition as input parameters. The proposed system, called Fuzzy-based System for Determining the Stress Feeling Level (FSDSFL), can invoke a certain action that improves the driver’s mood by providing the appropriate driving support. We show through simulations the effect of the considered parameters on the determination of the stress feeling level and demonstrate some actions that can be performed accordingly.
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References
Bylykbashi, K., Qafzezi, E., Ampririt, P., Ikeda, M., Matsuo, K., Barolli, L.: Performance evaluation of an integrated fuzzy-based driving-support system for real-time risk management in VANETs. Sensors 20(22), 6537 (2020). https://doi.org/10.3390/s20226537
Bylykbashi, K., Qafzezi, E., Ampririt, P., Ikeda, M., Matsuo, K., Barolli, L.: A fuzzy-based system for deciding driver impatience in VANETs. In: Barolli, L. (ed.) 3PGCIC 2021. LNNS, vol. 343, pp. 129–137. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-89899-1_13
Bylykbashi, K., Qafzezi, E., Ikeda, M., Matsuo, K., Barolli, L.: Fuzzy-based driver monitoring system (FDMS): implementation of two intelligent FDMSs and a testbed for safe driving in VANETs. Futur. Gener. Comput. Syst. 105, 665–674 (2020). https://doi.org/10.1016/j.future.2019.12.030
Hartenstein, H., Laberteaux, L.: A tutorial survey on vehicular ad hoc networks. IEEE Commun. Mag. 46(6), 164–171 (2008)
Kandel, A.: Fuzzy Expert Systems. CRC Press, Boco Raton (1991)
Klir, G.J., Folger, T.A.: Fuzzy Sets, Uncertainty, and Information. Prentice Hall Inc., Upper Saddle River (1987)
McNeill, F.M., Thro, E.: Fuzzy Logic: A Practical Approach. Academic Press, Cambridge (1994)
Munakata, T., Jani, Y.: Fuzzy systems: an overview. Commun. ACM 37(3), 69–77 (1994). https://doi.org/10.1145/175247.175254
SAE On-Road Automated Driving (ORAD) committee: Taxonomy and definitions for terms related to driving automation systems for on-road motor vehicles. Technical report, Society of Automotive Engineers (SAE) (2018). https://doi.org/10.4271/J3016_201806
Singh, S.: Critical reasons for crashes investigated in the national motor vehicle crash causation survey. Technical report (2015)
World Health Organization: Global status report on road safety 2018: summary. World Health Organization, Geneva, Switzerland (2018). (WHO/NMH/NVI/18.20). Licence: CC BY-NC-SA 3.0 IGO)
Zadeh, L.A., Kacprzyk, J.: Fuzzy Logic for the Management of Uncertainty. Wiley, New York (1992)
Zimmermann, H.J.: Fuzzy Set Theory and Its Applications. Springer, New York (1996). https://doi.org/10.1007/978-94-015-8702-0
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Bylykbashi, K., Qafzezi, E., Ampririt, P., Ikeda, M., Matsuo, K., Barolli, L. (2022). A Fuzzy-Based System for Safe Driving in VANETs Considering Impact of Driver Impatience on Stress Feeling Level. In: Barolli, L., Kulla, E., Ikeda, M. (eds) Advances in Internet, Data & Web Technologies. EIDWT 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 118. Springer, Cham. https://doi.org/10.1007/978-3-030-95903-6_25
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DOI: https://doi.org/10.1007/978-3-030-95903-6_25
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