Читать книгу Fog Computing - Группа авторов - Страница 15

The number of vehicles on the road is increasing every year as well as the number of road accidents [12]. In order to reduce or avoid the collision accident, academic and industrial researchers have been working on improving the safety aspect of the vehicles. Specifically, the advancement in communication technologies has allowed the development of advanced driver-assistance systems (ADAS), which has emerged as an active manner of preventing car crashes. ADAS has made many achievements through the development of systems that include rear-end collision avoidance and forward collision warning (FCW). The vehicle-to-vehicle (V2V) communication plays a big role in ADAS systems and it is manifested in ensuring that the controllers on board the vehicles (i.e. onboard unit, OBU) are capable of communicating with other vehicles for the purpose of negotiating maneuvers in the intersections and applying automatic control when it is necessary to avoid collisions [13]. The success of these systems relies a lot on the reliability of the communication. Therefore, many models of V2V communication have been investigated. Some of them focus on probabilities and analytic approaches in modeling the communication message reception while others adapt Markovian methods to assess the performance and reliability of the safety-critical data broadcasting in IEEE 802.11p vehicular network [14]. Vehicular ad-hoc network (VANET) has also contributed to integrate and improve the car-following model or platooning, which reduces the risks of collisions and makes the driving experience safer [15]. Explicitly, today's smart vehicular network systems have applied the fog computing mechanisms that utilize the cloud-connected OBUs of the vehicle to process the data from the onboard sensors toward exchanging context information in the vehicular network and participating in the intelligent transport systems.