Traffic Flow and Speed Monitoring Based On Optical Fiber Distributed Acoustic Sensor

In the realm of intelligent transportation systems, accurate and reliable traffic monitoring is crucial. Traditional devices, such as cameras and lidars, face limitations in adverse weather conditions and complex traffic scenarios, prompting the need for more resilient technologies. This paper presents traffic flow monitoring method using optical fiber-based Distributed Acoustic Sensors (DAS). An innovative vehicle trajectory extraction algorithm is proposed to derive traffic flow statistics. In the processing of optical fiber waterfall diagrams, Butterworth low-pass filter and peaks location search method are employed to determine the entry position of vehicles. Subsequently, line-by-line matching algorithm is proposed to effectively track the trajectories. Experiments were conducted under both real highway and tunnel scenarios, showing that our approach not only extracts vehicle trajectories more accurately than the classical Hough and Radon transform-based methods, but also facilitates the calculation of traffic flow information using the low-cost acoustic sensors. It provides a new reliable means for traffic flow monitoring which can be integrated with existing methods.