Real vehicle trajectory monitoring based on ultra-weak fiber Bragg grating distributed acoustic sensing and improved Hough transform

Subject of study. Ultra-weak fiber Bragg grating distributed acoustic sensing is an innovative technology with significant advantages. In this paper, a vehicle trajectory monitoring method based on ultra-weak fiber Bragg grating distributed acoustic sensing technology is proposed. Purpose of the work. The purpose is to achieve cost-effective, highly accurate, and efficient traffic monitoring through the use of the ultra-weak fiber Bragg grating distributed acoustic sensing technology and improved algorithms. Method. The method converts the vibration signals collected from buried road fiber optic cables into a spatio-temporal 2-dimensional vibration energy response using the Stockwell transform and enhances the vehicle vibration trajectory with the EDLines algorithm. The vehicle trajectory is then detected and extracted using the improved progressive probabilistic Hough transform algorithm. Based on the slope of the vehicle trajectory data, the task of estimating traffic flow and vehicle speed can also be accomplished. Main results. Experimental results demonstrate that the vehicle vibration signal can be significantly enhanced using the Stockwell transform and EDLines algorithms. The improved progressive probabilistic Hough transform algorithm increases the vehicle trajectory detection speed by 33% and the detection accuracy by 51% compared to the original algorithm. Simultaneously, the accuracy of traffic flow estimation exceeds 91%, and the accuracy of vehicle speed estimation exceeds 94%. Practical significance. This provides a viable solution for realizing efficient vehicle trajectory monitoring using the ultra-weak fiber Bragg grating distributed acoustic sensing system.