Research On Security Alert Algorithm In Vehicle Front Collision Avoidance System

The system of car front collision warning has attracted extensive attention of the whole society. As the important part of car’s active safety system, it can effectively prevent the traffic accidents and provide security alarm for the driver. Security Warning Decision is the current research hot spot, and the safe distance and speed between two vehicles, road traffic characteristics and the driver’s driving characteristics and other factors is the important support for the Security Warning Decision.In this paper, safety distance and speed between two vehicles, road conditions are the important research study in the Collision warning system. Firstly, the safety distance model is established based on the characteristics of the road before the car different longitudinal motion state, and analyze the impact of various parameters on the relationship between the safety distance by the classic vehicle braking process of kinematics analysis. In order to better solve the extremely and complex conditions in the process of vehicle driving, this paper analyzes the comfort of drivers, improve the safety distance model, and introduce a safe distance adjustment coefficient adaptation size and design non-emergency and emergency warning mode based on the natural drying cement or asphalt pavement conditions. We can obtain the parameters which approach the reality by introducing fuzzy theory and establishing fuzzy relationship factors affect the coefficient between the parameter values. For the data have some errors between the real situation and the fuzzy inference, this paper use particle swarm algorithm for online optimization of fuzzy system, and the fuzzy inference prediction values is more approximate value generated during the actual behavior of the driver, so the system have the learning and revise ability to achieve driver behavior and the system could reflect the characteristics of early warning systems. And the simulation results prove the feasibility of optimization methods. The experimental results show that car front collision warning system can reduce the driver "adaptation" to the driver and unnecessary alarm. Also the results show that the model and the parameters to determine the safety distance is reasonable. And the vehicles front collision warning system can provide a theoretical basis and reference for the hardware design.