Human intrusion detection for high-speed railway perimeter under all-weather condition

Abstract

PurposeThe paper aims to solve the problem of personnel intrusion identification within the limits of high-speed railways. It adopts the fusion method of millimeter wave radar and camera to improve the accuracy of object recognition in dark and harsh weather conditions.Design/methodology/approachThis paper adopts the fusion strategy of radar and camera linkage to achieve focus amplification of long-distance targets and solves the problem of low illumination by laser light filling of the focus point. In order to improve the recognition effect, this paper adopts the YOLOv8 algorithm for multi-scale target recognition. In addition, for the image distortion caused by bad weather, this paper proposes a linkage and tracking fusion strategy to output the correct alarm results.FindingsSimulated intrusion tests show that the proposed method can effectively detect human intrusion within 0–200 m during the day and night in sunny weather and can achieve more than 80% recognition accuracy for extreme severe weather conditions.Originality/value(1) The authors propose a personnel intrusion monitoring scheme based on the fusion of millimeter wave radar and camera, achieving all-weather intrusion monitoring; (2) The authors propose a new multi-level fusion algorithm based on linkage and tracking to achieve intrusion target monitoring under adverse weather conditions; (3) The authors have conducted a large number of innovative simulation experiments to verify the effectiveness of the method proposed in this article.

Current status and prospects of research on safety situation awareness of high speed railway operation environment

“…For railroad perimeter monitoring, Wen, Peng, Lin, Gan, and Tan (2024) designed a camera and LiDAR sensor fusion strategy for complex weather and foreign object intrusion detection, which shows the robustness under rain and snow conditions. For railroad perimeter intrusion monitoring, Guo, Shi, Ma, and Wang (2024) proposed a millimeter-wave radar and video fusion monitoring scheme and designed a "linkage þ tracking" fusion algorithm. These algorithms have significantly improved the coverage, applicable weather and recognition effect compared with the single-sensor technology (Wang, Liang, Liu, & Shi, 2020).…”