Driving style classification method for lane change warning system

Aiming at the different requirement of lane change warning system for different drivers with different driving style, vision sensor, radar, GPS, vehicle CAN bus data capture system are installed in a small passenger car, and real road driving test is carried out. Based on this, real road driving data of different drivers is collected. Following headway, lane change headway, overspeed frequency and max turning angle of steering wheel during lane change are selected as judge parameters, and fuzzy evaluation method is used to establish classification model of driving style in the way of offline. Drivers are divided into aggressive driver, relatively aggressive, relatively cautious and cautious. Parameters related to lane change safety are used to verify the classification model, and the results show that with the increasing of cautious level, the lane change safety parameters are inclined to safely correspondingly. The consistency between driving style classification model and lane change safety real judge parameters is good.