Traffic volume measurement based on a single smart road stud

Abstract Anisotropic Magneto-Resistive (AMR) sensing is one of the most burgeoning techniques for traffic volume measurement to support effective traffic management. This is because of its small size, low power consumption and environmental resilience. This paper presents a vehicle detection algorithm based on a new type of AMR sensor called Smart Road Stud (SRS), which can detect the Magnetic Field Intensity (MFI) disturbance generated by passing vehicles. The proposed two-step process can extract the disturbance signal from MFI time series with a simple determination of threshold and a more widespread applicability. However, when vehicle temporal headway is short, an extracted signal may be generated by more than one vehicle. For this case, a method to recognize the number of vehicles the signal corresponds to is proposed also. The results show that the accuracy of traffic volume measurement is higher than 97% when detecting traffic volume in two adjacent lanes.