Railway Intrusion Detection Based on Machine Vision: A Survey, Challenges, and Perspectives

被引:5
|
作者
Cao, Zhiwei [1 ,2 ]
Qin, Yong [1 ,2 ]
Jia, Limin [1 ,2 ]
Xie, Zhengyu [1 ,2 ]
Gao, Yang [1 ,2 ]
Wang, Yaguan [3 ]
Li, Ping [4 ]
Yu, Zujun [5 ]
机构
[1] Beijing Jiaotong Univ, State Key Lab Adv Rail Autonomous Operat, Key Lab Railway Ind Proact Safety & Risk Control, Beijing 100044, Peoples R China
[2] Beijing Jiaotong Univ, Sch Traff & Transportat, Beijing 100044, Peoples R China
[3] Beijing Mass Transit Operat Co Ltd, Beijing 100044, Peoples R China
[4] China Acad Railway Sci, Beijing 100081, Peoples R China
[5] Beijing Jiaotong Univ, Sch Mech Elect & Control Engn, Beijing 100044, Peoples R China
关键词
Rail transportation; Intrusion detection; Monitoring; Machine vision; Inspection; Autonomous aerial vehicles; Object detection; Railway safety; intrusion detection; obstacle detection; machine vision; machine learning; deep learning; OBSTACLE DETECTION; DETECTION SYSTEM; CAMERA; TRACKS; ALGORITHM;
D O I
10.1109/TITS.2024.3412170
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Railway intrusion seriously threatens railway safety and can cause enormous loss of life and property. Therefore, railway intrusion detection is crucial for the safety of railway operation. Among the current methods of intrusion detection, machine vision-based methods have been widely used in railways, and have attracted close attention because of their great benefits. This paper proposes a comprehensive review of railway intrusion detection based on machine vision, covering ground monitoring, on-board inspection, and unmanned aerial vehicle (UAV) inspection. First, this paper systematically reviews most of the studies over the past two decades and presents the survey in three parts. Second, by analyzing these studies and the requirements for railway monitoring, we summarize the major challenges that hinder railway intrusion detection based on machine vision. Finally, we propose several promising perspectives for railway intrusion detection based on machine vision by comprehensively considering the development of machine vision, sensors, and pattern recognition together with the needs of railway scenes.
引用
收藏
页码:6427 / 6448
页数:22
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