Effect of vehicle technical condition on real-time driving risk management in Internet of Vehicles: Design and performance evaluation of an integrated fuzzy-based system

Abstract

With the new era of Internet of Things (IoT), the Internet of Vehicles (IoV) is well on its way from just a concept to a reality over the next few years. IoV promises to enable a myriad of vehicular applications and is committed to providing road safety above all things. However, to take full advantage of IoV, an adequate coordination between IoV, the emerging technologies and the existing ones must be achieved. In this paper, we show how these technologies help existing and future driving-support systems and propose an integrated fuzzy-based driving-support system for real-time risk management that considers many parameters, including the vehicle technical condition (VTC). The proposed system considers the current condition of parameters that could impact the driver and the vehicle performance to assess the risk level. The parameters include the vehicle speed, weather and road condition, and factors that affect the driver’s ability to drive, such as his/her current health condition and the inside environment in which he/she is driving, in addition to the VTC. The data for input parameters can come from different sources, such as on-board and on-road sensors and cameras, and from communications between vehicles and infrastructure based on the penetration of IoV. We show through simulations the effect of the considered parameters on the evaluation of the driving risk and demonstrate a few actions that can be performed accordingly. When the risk remains less than 0.2 the driving situation is marked as safe, otherwise an alarm is generated and the appropriate actions are taken. A VTC less or equal than 0.5 causes an alarm even if all the other parameters are in good conditions.