基于智能视频分析的铁路客运站运营态势感知技术及应用

Operational Situation Awareness Technology for Railway Passenger Stations Based on Intelligent Video Analysis

人工监控铁路客运站极易出现视觉疲劳,降低时效性和准确性,为此提出一种基于智能视频分析的铁路客运站运营态势感知技术。该技术深度结合生产作业计划,基于AI人工智能算法,分别针对站台和候车厅提出站台异常行为检测模型和站厅客流运动态势分析模型。采用基于自适应特征金字塔的二级级联网络,提取站台上的游荡人员/行李并判断目标所处的位置及轨迹,实现站台越线、端部入侵、警戒区域徘徊、标准化作业、工作人员到岗等功能;采用基于跨域残差空间全卷积网络对远景的候车厅/通廊等场景自动生成人群热力密度图和移动态势图,对近景的进站口/检票口等场景自动评估排队及候检情况。根据站内的客流密度和异常态势,智能调配客运人员的作业计划,提高旅客出行体验和候车安全性。

It is highly susceptible to visual fatigue for manual surveillance of railway passenger stations,leading to decreased timeliness and accuracy.Therefore,this paper proposed a technology for operational situation awareness of railway passenger stations based on intelligent video analysis.This technology based on an artificial intelligence algorithm that deeply combined production and operation plans.It provided abnormal behaviors detecting models on platforms and analyzed passenger flow movement patterns in waiting halls respectively.It extracted wandering personnel/luggage on the platform and determined the location and trajectory of the target based on the adaptive feature pyramid two-stage cascaded network,achieving functions such as platform crossing detection,end intrusion detection,wandering in restricted areas,standardized operations,and staff attendance verification.The technology automatically generated crowd density heatmaps and movement pattern maps based on the cross-domain residual spatial fully convolutional network in situations such as the waiting hall/corridor in the foreground.Additionally,it automatically assessed queuing and inspection situations for scenarios such as nearby entrances and ticket gates.The technology intelligently adjusts the operational plans of passenger service staff,enhancing both the travel experience and waiting safety for passengers,based on the passenger flow density and abnormal situations within the station.