基于小波和模糊逻辑理论的交通事件检测

摘要

为提高高速公路交通事件检测算法的检测率,提出一种基于小波和模糊逻辑理论的检测算法.使用小波理论的小波变换和改进的滤波算法检测交通事件,得到事件可能发生的时间和地点;以模糊逻辑理论修正算法输出,建立交通参数隶属度函数,通过计算给出最终事件判定结果及交通拥堵状态.仿真结果表明,对比其它多种先进的检测算法,该算法在检测率和误报率等指标上有明显优势,平均提高事件检测率4%左右,具有更好的鲁棒性.%To improve the detection rate of freeway traffic incident detection algorithm,an algorithm based on wavelet theory and fuzzy logic theory was proposed.The wavelet transform and improved filtering algorithm were used to detect traffic incident,to obtain the time and place of the incident.Fuzzy logic theory was used to amend the output of the detection algorithm,and the final results and state of traffic congestion were achieved by calculating the traffic parameters membership functions.Compared with some advanced detection algorithms,simulation results show that the detection algorithm has obviously advantages over detection rate and false alarm rate,and the detection rate can be improved by 4% on average with better robustness.