Agent based Assistance System with Ubiquitous Data Mining for road safety
Karuna C. Gull, Amrita Mogali · 2009
The number of accidents caused every year in India is disastrously high 95% of these are attributed to drivers' errors. Risk assessment is at the core of the road safety problem. This paper presents an advanced driving assistance system (ADAS), called ABASUR, that analyses situational driver behavior and proposes real-time countermeasures to minimize fatalities/casualties. The system is based on ubiquitous data mining (UDM) concepts. It fuses and analyses different types of information from crash data and physiological sensors to diagnose driving risks in real time. The novelty of our approach consists of augmenting the diagnosis through UDM with associated countermeasures based on a context awareness mechanism. In other words, our system diagnoses and chooses a countermeasure by taking into account the contextual situation of the driver and the road conditions. The types of context we exploit include vehicle dynamics, drivers' physiological condition, driver's profile and environmental conditions. The system, thus aims at proposing an innovative, intelligent system which aids the drivers take a proper decision to pre-decide their next move, hence reducing drastically the probability of many road accidents.