Detection, classification, and characterization are the key to enhancing motorcycle safety, motorcycle operations and motorcycle travel estimation. Average motorcycle fatalities per Vehicle Mile Traveled (VMT) are currently estimated at 30 times those of auto fatalities. Although it has been an active research area for many years, motorcycle detection still remains a challenging task. Working with FHWA, we have developed a hybrid motorcycle detection and counting system using a suite of sensors including stereo camera, thermal IR camera and unidirectional microphone array. The IR thermal camera can capture the unique thermal signatures associated with the motorcycle’s exhaust pipes that often show bright elongated blobs in IR images. The stereo camera in the system is used to detect the motorcyclist who can be easily windowed out in the stereo disparity map. If the motorcyclist is detected through his or her 3D body recognition, motorcycle is detected. Microphones are used to detect motorcycles that often produce low frequency acoustic signals. All three microphones in the microphone array are placed in strategic locations on the sensor platform to minimize the interferences of background noises from sources such as rain and wind. Field test results show that this hybrid motorcycle detection and counting system has an excellent performance.
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