Dangerous Event Analysis Subsystem of Driver Assist System

[[abstract]]To help provide safety for drivers, many driver assistance systems (DAS) have been developed. Various kinds of devices are used in DAS. Some devices have been installed in cars, like air bags, antilock braking system (ABS), and backup radar. Some descriptions of other devices have recently been published, such as the crossing-lane sensor and a alcohol sensor. And some devices are still in research, such as road sign sensors. Such devices work independently of each other and, as a result, indicate when drivers become distracted from their primary task of driving or are tired. For this reason, this paper proposes a system to integrate the outputs of these devices and to provide a warning to drivers. First, the dangerous driving event analysis system using fuzzy rough sets to reduce the attributes is presented. Then the system selects the important rules depending on the representation and confirmation of the rules from the reduced data. Finally, the system using fuzzy Petri nets to form the reasoning module from a set of rules we derive determines if there is a danger. Thereby, the driver is warned, and the accident can be prevented.