Abandoned objects detection on the highway based on distributed features of UWFBG array sensors

Real-time monitoring of abandoned objects on the highway, with limitless vision and adaptability to diverse weather or lighting conditions, is essential for the Intelligent Transportation System (ITS). This paper proposes a method to identify the abandoned objects based on distributed features of ultra-weak fiber Bragg grating (UWFBG) array sensors. In the field experiment conducted in a real highway, the UWFBG array vibration sensing cables were utilized to capture vibration signals generated by the abandoned object dropped from the vehicle. The signal processing algorithm, including intensity mapping, filtering and self-developed extraction algorithm, are deployed to map and extract the signal features of abandoned objects, and the high-efficient identification and localization extracted from the massive noisy data are approached. The analysis results demonstrate that the proposed method can accurately identify abandoned objects on the highway, without any interference by poor lighting or inclement weather condition.