Shi Tianyun, Guo Pengyue, Wang Rui, Ma Zhen, Zhang Wanpeng, Li Wentao, Fu Huijin, Hu Hao
China Academy of Railway Sciences, 2 Daliushu Road, Haidian District, Beijing 100081, China.
Institute of Electronic Computing Technology, China Academy of Railway Sciences, 2 Daliushu Road, Haidian District, Beijing 100081, China.
Sensors (Basel). 2024 Aug 23;24(17):5463. doi: 10.3390/s24175463.
In recent years, the safety issues of high-speed railways have remained severe. The intrusion of personnel or obstacles into the perimeter has often occurred in the past, causing derailment or parking, especially in the case of bad weather such as fog, haze, rain, etc. According to previous research, it is difficult for a single sensor to meet the application needs of all scenario, all weather, and all time domains. Due to the complementary advantages of multi-sensor data such as images and point clouds, multi-sensor fusion detection technology for high-speed railway perimeter intrusion is becoming a research hotspot. To the best of our knowledge, there has been no review of research on multi-sensor fusion detection technology for high-speed railway perimeter intrusion. To make up for this deficiency and stimulate future research, this article first analyzes the situation of high-speed railway technical defense measures and summarizes the research status of single sensor detection. Secondly, based on the analysis of typical intrusion scenarios in high-speed railways, we introduce the research status of multi-sensor data fusion detection algorithms and data. Then, we discuss risk assessment of railway safety. Finally, the trends and challenges of multi-sensor fusion detection algorithms in the railway field are discussed. This provides effective theoretical support and technical guidance for high-speed rail perimeter intrusion monitoring.
近年来，高速铁路的安全问题依然严峻。过去，人员或障碍物闯入铁路周边区域的情况屡有发生，导致列车脱轨或停车，尤其是在雾、霾、雨等恶劣天气条件下。根据以往研究，单一传感器难以满足所有场景、所有天气和所有时域的应用需求。由于图像和点云等多传感器数据具有互补优势，高速铁路周边入侵的多传感器融合检测技术正成为研究热点。据我们所知，目前尚无关于高速铁路周边入侵多传感器融合检测技术的研究综述。为弥补这一不足并推动未来研究，本文首先分析高速铁路技术防范措施的情况，总结单传感器检测的研究现状。其次，在分析高速铁路典型入侵场景的基础上，介绍多传感器数据融合检测算法和数据的研究现状。然后，我们讨论铁路安全风险评估。最后，探讨铁路领域多传感器融合检测算法的发展趋势和挑战。这为高铁周边入侵监测提供了有效的理论支持和技术指导。
