Fibre Optic Acoustic Sensing (FOAS) for Automatic Traffic Jam Queue End Detection

Queue end detection in traffic jams is especially important on highways that are prone to traffic jams and to fog or other severe weather that can significantly reduce visibility. An automatic warning system for traffic jam build-up needs to work seamlessly over the whole affected road section. In line with this, we introduce fibre optic acoustic sensing (FOAS) for automated queue end detection in traffic jams. In FOAS systems, series of light pulses are transmitted along a fiber-optic cable and the back-scattered light, which is affected by the mechanical strain of the fiber-optic cables due to ground vibrations, is measured and analyzed. With fiber-optic cables installed parallel to a highway where ground vibrations are induced by passing vehicles, traffic information such strong deceleration can be detected in the FOAS signals. In this paper, we present an algorithm based on image processing methods that estimates strong braking action from image representations generated from FOAS signals. We tested the results of the algorithm on FOAS data collected on a real highway.