车辆碰撞信号插值补偿算法仿真

摘要

为了解决由于车辆碰撞造成的道路拥堵、连续追尾事故的发生,研究了车辆碰撞信号检测方法,以Q-L在线进化学习的车辆碰撞信号插值补偿算法为估算方法对车辆的行驶状态进行碰撞系数计算,通过在线进化的最优近似算法来寻找当前车辆行驶状态的最优插值数据区间,寻找具有最优反馈值和评价函数值的执行状态参数,从而得到车辆碰撞参数.以车辆碰撞测试中的碰撞数据和正常数据进行融合,作为仿真的输入数据,在不同信噪比下对算法的有效性进行仿真,结果表明,插值补偿算法具有较好的鲁棒性,检测率较高,误报率较低.%In order to solve the road congestion caused by vehicle collision and continuous rear-end accidents,the method of vehicle collision signal detection was studied,the coefficient of the traveling state of the vehicle collision was calculated by QL evolution of online learning vehicle collision signal interpolation compensation algorithm for estimation method,and the online evolutionary optimal approximation algorithm was used to find the current optimal vehicle status interpolation data interval and look for the execution status parameter which has an optimal feedback value and the evaluation function value and result in vehicle collision parameters.With the vehicle collision crash test of collision data and normal data to be integrated as the simulation of the input data,the effectiveness of the algorithm were simulated in different signal-to-noise ratios.The results show that the interpolation compensation algorithm is robust,the detection rate is high,and the false alarm rate is low.