Study On Vehicle Anti-collision Forewarning Technology Based On Multi-information Detection

With the rapid development of automotive industries and highways,the car ownership of our country keeps increasing and traffic accidents happen frequently.In order to enhance the security of vehicles and reduce traffic accidents and casualties,great importance has been attached to vehicle anti-collision forewarning technology by more and more researchers.The technology is a kind of driving support technology which is able to realize the anti-collision driving by taking appropriate measures through the analysis and prediction of possible accidents.Therefore,studying on vehicle anti-collision forewarning technology is helpful to reduce the driver's psychological burden and improve driving security.At present,most experts pay more attention to the study of lane departure warning and the maintenance of safe distance between vehicles.However,it's very significant to analyze the driver's fatigue driving behavior.Therefore,the paper studies driver's fatigue driving behavior as well as lane departure warning and the maintenance of safe distance from the three aspects of people-car-road.Firstly,the technology of the lane departure warning is investigated and the TLC(Time to Lane Crossing)algorithm is proposed.At the same time,the model of lane departure warning algorithm is established and the driveway is divided into 4 regions to achieve different levels of forewarning.In order to verify the reliability of the proposed algorithm,this paper carries out both simulation analysis and real vehicle test.Secondly,a thoughtful test program is designed and the steering characteristics in different driving states through a complete vehicle experiment are obtained.In order to verify the relationship of steering and fatigue driving,the steering changes in both states of awake driving and fatigue driving are analyzed by using steering angle and steering entropy method.The method of judging fatigue driving behavior is given at last.Further,the simplest model of braking distance based on the analysis of vehiclebraking process is improved.At the same time,the model of minimum safe distance during driving process is established.The validity of minimum safe distance model is verified by joint simulation in CARSIM and MATLAB/SIMULINK.Finally,the model of the Federal Kalman Filter algorithm is established to achieve the information fusion of millimeter wave radar and camera.And the simulation is conducted and the results show that the vehicle anti-collision detection technology based on the information fusion is effective and the accuracy of the system is improved.