Research And Design Of The Detection And Alarm System For Vehicle Collision

People's lives become more convenient with the advent of the automobile era.Cars have already become a necessity for people's lives.However,the occurrence of traffic accidents becomes more frequent and seriously threatens people's lives due to the increase of the cars' number,the complexity of road conditions and serious environmental problems.Automobile safety has become a major issue to be solved.With the rapid development of intelligent transportation systems and intelligent vehicles,the research of vehicle crash detection and alarm system has gradually attracted the attention of some scientific research institutions.This system is mainly used to detect whether the accident occurred and confirm the emergency alarm after the accident,which can significantly reduce the waiting time of the rescue and people's property losses.Therefore,we study and design a vehicle crash detection and alarm system to reduce casualties in this paper.In this thesis,a fuzzy adaptive multi-sensor data fusion algorithm is designed to process vehicle sensor information.Only the federal kalman filter is commonly used in vehicle collision detection scenarios among the existing multi-sensor data fusion algorithms.However,the premise of federal kalman filter is based on the assumption that the measurement noise is Gaussian white noise,while the variability of vehicle operating environment causes the complex and changeable measurement noise.So the main research objectives of this thesis is to adjust the measurement noise adaptively,in which we consider using the feedback coefficient which can be obtained through fuzzy inference system.Taking into account the existence of defect and need to deal with accidents,we designed a new multi sensor data fusion algorithm combining federal kalman filter,fuzzy inference system,defects processing and accident judging module.The results of Matlab simulation show that the proposed algorithm can improve the accuracy within a small delay,which can be improved by adding the algorithm reset mechanism.Therefore,the new algorithm we designed is well performed.A new vehicle crash detection and alarm system which uses the above designed data fusion algorithm is also designed in this thesis.The system includes Android-based phone terminal and OBCU terminal based on C language.Mobile phone terminal and OBCU terminal respectively contain different information modules and interactive modules.The two terminals process data and detect accidents at the same time.The accident is confirmed if they both detect the accident within a small delay.Then our system interacts with the users and determines whether the need for alarm.Through the simulation in the laboratory test scene,we found that this system can accurately determine the scene of crash accidents,although there may be non-crash scenes of small probability of wrong judgment,but the interface of the mobile phone could remind user to determine non-accident incident.And the entire system is cheap and independent of the vehicle,which means our system is quite cost-effective.