[[alternative]]Driver Assistance System–Dangerous Driving Event Analysis Subsystem

[[abstract]]To help provide safety for drivers, driver assistance systems have been an area of active research in recent years. An important component in such systems are detection subsystems. Many have been developed based on various technologies. These detection subsystems always work independently of each other and, as a result, there are often conflicts regarding the detection of objects by these diverse systems. Also, these subsystems often make needless warnings to drivers, causing the drivers to be distracted from their primary task of driving. With this in mind, this paper proposes a system to integrate the results of detection subsystems and provide a better organized and filtered set of commands or suggestions to drivers. Collecting realistic hazardous driving events on freeways is difficult and dangerous, so we set up a freeway driving simulation system provide usable data (both common and dangerous events encountered while driving) for use with our detection subsystem. The dangerous driving event analysis subsystem analyzes and infers driving events using a CFRPN (cascaded fuzzy reasoning Petri net) module, and then determines if it is a danger. If so, then the driver is warned. The experimental results show that this proposed approach is feasible. If the dangerous driving event analysis subsystem is incorporated into a driver assistance system, a driver can drive more easily and safety will be improved.