Abstract
In this paper, we propose and implement an intelligent system based on Fuzzy Logic (FL) for deciding driver impatience in VANETs. The proposed system, called Fuzzy-based System for Deciding Driver Impatience (FSDDI), considers parameters that have a strong impact on the driver impatience. The input parameters include the driver’s emotional condition, the time pressure and the number of route stops. Based on the driver impatience output value, the system can invoke a certain action, which aims at improving 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 driver impatience and demonstrate some actions that can be performed accordingly.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
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., 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 (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 (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 Science & Business Media, New York (1996). https://doi.org/10.1007/978-94-015-8702-0
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Bylykbashi, K., Qafzezi, E., Ampririt, P., Ikeda, M., Matsuo, K., Barolli, L. (2022). A Fuzzy-Based System for Deciding Driver Impatience in VANETs. In: Barolli, L. (eds) Advances on P2P, Parallel, Grid, Cloud and Internet Computing. 3PGCIC 2021. Lecture Notes in Networks and Systems, vol 343. Springer, Cham. https://doi.org/10.1007/978-3-030-89899-1_13
Download citation
DOI: https://doi.org/10.1007/978-3-030-89899-1_13
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-89898-4
Online ISBN: 978-3-030-89899-1
eBook Packages: EngineeringEngineering (R0)