基于TMR传感器的车辆检测分类算法研究

Research on vehicle detection and classification algorithm by TMR sensor

车辆检测与分类是智能交通运输系统研究的核心技术之一,具有广泛的应用前景。深入研究了隧穿磁阻(Tunneling Magneto Resistance,TMR)传感器的产生机理,结合双节点动态采样机制以及车辆波形窗口斜率拐点的加权欧氏距离算法,提出了一种基于TMR传感器的车辆检测技术。经道路车辆检测数据显示,与感应线圈检测法等相比,该检测方法功耗低、使用寿命长,且不易受外界环境影响,能实时、精确地检测车流量及速率,完成车辆类型的识别与分类。

Vehicle detection and classification is one of the key techniques in intelligent transportation system, and it has a broad application prospect. This paper studies the working mechanism of tunneling magneto resistance(TMR) sensor, and proposes a TMR sensor based vehicle detection technique by combining the double point dynamic sampling mechanism and the weighted Euclidean distance method for knee slopes of vehicle waveform. The experiments of road vehicle detection show that the feature of this detection method is low power consumption and long service life comparing with the induction coil detection; and it is not easily affected by external environment. Moreover, it can detect the vehicle flow and speed accurately and complete the identification and classification of vehicle types.