Research On Key Technologies For Intelligent Perception Of Passenger Flow Safety Status In Metro Station Based On Video Surveillance

As the pace of urbanization is getting faster and faster in China,the pressure on cities caused by transportation is also increasing.Metro travel has become the preferred mode of transportation for more and more public travelers due to its advantages such as convenience,fast speed,large traffic volume and punctual departure time.As an important node of urban rail transit lines,metro stations bear the pressure of gathering and distributing passenger flow of rail transit.It is easy to cause heavy passenger flow congestion,causing potential safety hazards.At present,the video monitoring system of metro stations in our country still lacks in the arrangement of video monitoring and acquisition equipment and the level of detection intelligence,which is difficult to content the needs of intelligent perception of the safety status of metro station passenger flow.Under this background,through the research on economical and reasonable camera layout method,high accuracy passenger flow information detection algorithm,reasonable and effective passenger flow safety status level assessment and early warning,scientifically realize the intelligent perception of metro station passenger flow security status.According to the needs of the layout of the metro station passenger flow information collection equipment,a method for grading the layout of the metro station video surveillance collection equipment is proposed.Using the layout model of video surveillance collection points based on regular hexagon area segmentation,an example analysis of the layout of video surveillance collection equipment at a metro station in a province.It has a guiding significance for the placement of subsequent video monitoring and acquisition equipment.Aiming at the needs of passenger flow information detection,combined with metro station scenarios and passenger flow characteristics,a method for detecting passenger flow information of metro stations based on YOLO-v3 is proposed.The scene data set of a metro station was used for testing to verify that the algorithm meets the requirements of fast detection speed and high recognition accuracy.According to the needs of metro station passenger flow safety level assessment and warning and the basis of metro station passenger flow safety status grade evaluation,statistics of passenger flow density and passenger flow in each monitoring area are realized.The regional passenger flow density and passenger flow are used as the key indicators to classify levels to achieve passenger flow safety status level assessment and early warning level judgment.Through the research on key technologies of intelligent perception of passenger flow safety status in metro station based on video surveillance,this article can provide data support for the assessment of the safety status of passenger flows in metro stations.It can provide data support for the evaluation of the passenger train safety status level of the metro station,and provide a theoretical basis for the determination of the warning level of the large passenger flow.It has important practical significance for ensuring the safe operation of the urban rail.