A Tolerant Context-Aware Driver Assistance System for VANETs-Based Smart Cars

Current driver assistance systems merely use a minimum amount of information. By using additional information of the environment hazardous situations can be detected earlier, more reliably and with a higher accuracy. This situational information has a significant impact not only on hazard detection, but also on other modules such as the human-machine-interface or knowledge distribution between vehicles over vehicular ad-hoc networks. In this paper, we design TOCADAS (TOlerant Context-Aware Driver Assistance System) in order to help prevent accidents and reduce the number of traffic fatalities. The proposed TOCADAS is aware of uncertain situational information, recognizes current context situation and provides drivers with the most effective driver assistance services for the current context situation using pattern similarity degrees.

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