| Massive casualties and economic losses are caused by traffic accidents every year,which has become an important social issue across the globe.Pre-crash system can achieve a better occupant protection performance by controlling the occupant restraint system and other safety devices through its precise prediction and accurate judge of the coming collision prior to the crash accident.Traditional pre-crash systems suffer from several problems such as a low accuracy of judging the crash and the incapacity of optimizing and controlling the occupant restraint system according to the pre-detection information.In order to solve these problems,a pre-crash system framework is proposed in this study.Some key issues,which include how to improve the accuracy of target recognition and measurement for the sub-system of sensors,how to make sure that the pre-crash prediction is accurate and robust and how to estimate the crash pulse and thus optimize the control of occupant restraint system based on the pre-crash prediction information,are studied and possible solutions are presented to further improve the protection effect of traditional vehicle passive safety devices.In this study,demand analysis is firstly realized according to the features of the desired pre-crash system.On the basis of the result,a frame is established for the pre-crash system.Features of different parts are separated and studied to clarify their relationship,and then several key problems are researched one by one.In this paper,millimeter-wave radars(MMW radars)and cameras are used as external vehicle sensors.The data collected are properly analyzed.On this basis,a target recognition method using MMW radars and cameras is proposed to detect the target and cross-verify the information,in which way the target recognition rate and target window accuracy are increased.How to measure distance through cameras is studied to obtain the exact transverse position and dimension of the target vehicle,which supplements the information acquired from the radars.Combining the vehicle external information and the vehicle self-dynamicstatus and taking the critical braking and turning conditions into account,a subtle calculation model is established to work out the key time parameters during crash,as a result of which,it is possible to judge the danger of ego-vehicle accurately.Through geometric and kinetic calculation,the relative crash velocity,the possible crash position and time for an inevitable crash accident can be estimated precisely.The pre-crash algorithm in this study also takes calculation efficiency and system robustness into consideration.In the end,assuming that the stiffness of vehicle structure is in positive proportion to vehicle mass,the energy absorbed by the ego-vehicle during crash can be estimated according to the collision information and the size of target vehicle and the crash acceleration can be estimated in an accurate way using the relations between the vehicle structure deformation and its energy absorption and the discipline of acceleration responses of the vehicle body.With these inputs,the occupant restraint system model is verified to realize the optimized control of the occupant restraint system based on a specific crash accident and thus effectively reduce the injury of driver during the crash accident.In this study,a comprehensive simulation model of pre-crash system is established and part of it,which is of no safety risks,is verified against the experiment results.The simulation results indicate that the pre-crash system proposed in this study can accurately recognize various kinds of frontal crashes.The optimized control for the motorized seat belt is also employed within this system so as to effectively reduce the injury risks of drivers.The pre-crash system and its control strategy in this study are of great value and can be put into many practical applications. |
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