Research On Visualization Method Of Abnormal Traffic Flow In Metro Network

In recent years,with the acceleration of China's urbanization,a large number of people have flooded into cities,resulting in an increase of passenger traffic flow in megacities such as Beijing and Shanghai.The urban metro system has become a highspeed,efficient,and safe feature and the most important mode of transportation for megacities.In order to cope with the increasing traffic flow,the metro lines have increased sharply,and the metro network has become more and more complex.Some abnormal passenger flow events may have serious impact on the metro system and rapidly spread,seriously affecting residents' normal travel and personal safety.At present,although there are a large number of visualization researches on abnormal traffic flow,most of the researches are only for road network.Even if there are some visualization researches of metro abnormal passenger flow,the focus is mainly on abnormal stations,and the sections between stations are usually ignored.In addition,few existing researches can exploit the causes of metro abnormal passenger flow events in social media data through visualization.Aiming at the above problems,based on the metro smart card data and microblog data,this paper proposes a set of interactive visualization analysis method.This method not only organizes,analyzes and visualizes the spatio-temporal data related to abnormal stations and abnormal sections,but also helps users quickly find out the causes of the metro abnormal passenger flow events.The contributions of the paper are as follows:(1)A multi-dimensional visualization method for metro abnormal passenger flow based on metro smart card data is proposed.The visualization method can interactively present the abnormal spatio-temporal data in the metro system,thereby helping users verify the rationalities of the abnormal passenger flow of the station,discover the abnormal section flow on the metro line,and further reveal the propagation law of the anomalies in the entire metro system.(2)A visualization method for exploring the causes of metro anomalies based on Weibo data is proposed.The visualization method visually analyzes the microblog topic through various interactive views,so as to effectively help users quickly understand the specific causes of the abnormal traffic flow events in the massive microblog data.(3)Designed and implemented a visualization analysis system.The system integrates the above two visualization methods and provides a flexible interaction mode to help users complete the abnormality detection,abnormality verification,mastering the abnormal diffusion law and exploration of the causes of abnormal events in metro system.Finally,the paper uses a lot of cases with real data to prove the feasibility and efficiency of the proposed visualization method.The results show that the system for the metro system can provide a comprehensive visual analysis method for the relevant departments to analyze the influence and regularity of metro anomalies.