Frontal accidents severity anticipation by logistic regression model and effective parameters assessment

Accident severity modeling is an important object in accidents safety researches. This research consider to frontal accidents severity investigation and driver traumatism severity the informations of this research are consist of frontal accidents that two vehicle have one occupant. So, we use logistic regression method. This method determine which driver have more injury. Investigated variants are vehicles dynamic and static features, safetybelt, airbag and possibility of driver body egress of vehicle. Model processing shows logistic regression model has high authority in accidents severity anticipation. With elasticity environs and border cost dubitation formation, we investigated parameters role in frontal accident severity and finally have determined safety belt, airbag and vehicle weight are main roles in drivers traumatism likelihood abatement. The factors increase driver traumatism likelihood are high speed and driver body egress of vehicle. Vehicle size has no affection in safety increasing in frontal accidents.