On-line aggressive driving identification based on in-vehicle kinematic parameters under naturalistic driving conditions

Aggressive driving, amongst all driving behaviors, is largely responsible for leading to traffic accidents. With the objective to improve road safety, this paper develops an on-line approach for vehicle running state monitoring and aggressive driving identification, using kinematic parameters captured by the in-vehicle recorder under naturalistic driving conditions. To characterize the roads in reality, a novel road conceptual model is proposed. It accounts for not only the curve on the horizontal plane but also the slope on the vertical plane, as well as the cross slope. For each position where the vehicle is driving, the vehicle motion is decomposed into two circular motions on the horizontal and vertical planes. On each plane, the vehicle maneuver is first identified. Then, aggressive driving is identified according to the limit equilibrium of driving safety or comfortability. Based on the proposed method called “three-elements”, the vehicle maneuver, radius and slope angle on the vertical plane can be solved in an on-line manner. The novel approach is an elaborate analytical model with clear physical meaning but small computation load, and therefore is potential to be implemented in the mobile devices to assist in real-time aggressive driving identification and labeling. The developed approach is applied to a real case on the curved and sloped route in Nanjing, China. Empirical results of extensive experiments, based on the kinematic parameters collected from the in-vehicle data recorder under naturalistic driving conditions, demonstrate that aggressive driving behaviors are mostly found on the pavements with curve and slope, and can be identified by the developed approach.