Abstract
Vehicular Ad hoc Networks (VANETs) have gained great attention due to the rapid development of mobile internet and Internet of Things (IoT) applications. With the evolution of technology, it is expected that VANETs will be massively deployed in upcoming vehicles. In addition, ambitious efforts are being done to incorporate Ambient Intelligence (AmI) technology in the vehicles, as it will be an important factor for VANET to accomplish one of its main goals, the road safety. In this paper, we propose an intelligent system for safe driving in VANETs using fuzzy logic. The proposed system considers in-car environment data such as the ambient temperature and noise, vehicle speed, and driver’s heart rate to assess the risk level. Then, it uses the smart box to inform the driver and to provide better assistance. We aim to realize a new system to support the driver for safe driving. We evaluated the performance of the proposed system by computer simulations and experiments. From the evaluation results, we conclude that the vehicle’s inside temperature, noise level, vehicle speed, and driver’s heart rate have different effects on the assessment of risk level.
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Bylykbashi, K., Qafzezi, E., Ikeda, M., Matsuo, K., Barolli, L. (2020). A Fuzzy-Based System for Driving Risk Measurement (FSDRM) in VANETs: A Comparison Study of Simulation and Experimental Results. In: Barolli, L., Hellinckx, P., Natwichai, J. (eds) Advances on P2P, Parallel, Grid, Cloud and Internet Computing. 3PGCIC 2019. Lecture Notes in Networks and Systems, vol 96. Springer, Cham. https://doi.org/10.1007/978-3-030-33509-0_2
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DOI: https://doi.org/10.1007/978-3-030-33509-0_2
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