Research On Network Vulnerability Assessment And Collaborative Operation Management For Urban Rail Transit Emergencies

Urban rail transit emergencies not only seriously affect the travelling experience of passengers,but also have safety risks such as crowding and trampling.In order to improve the risk resistance capacity of the rail transit system and enhance the passenger service levels,it is necessary to identify the impact of the evolution of emergencies on passenger flow,to identify system weaknesses and formulate prevention and control plans,and to take scientific and reasonable disposal measures during the course of the incident.Focusing on passenger flow,this paper first analyzes the characteristics of emergencies and constructs an operational collaborative prevention and control system based on consideration of the complexity of rail transit systems.Furthermore,research on key issues such as passenger flow distribution estimation,network vulnerability assessment,and collaborative operation management in the collaborative prevention and control system are carried out.The specific research content includes:(1)Due to the complexity of passenger behavior under emergencies,in existing research the model-driven methods are difficult to identify the actual passenger flow distribution,while the data-driven methods have shortcomings in identification accuracy.In order to finely analyze the passenger flow distribution under emergencies,a passenger spatial-temporal trajectory identification algorithm is designed based on AFC and train operation data.Firstly,passengers are classified according to travel path complexity.By mining the passenger-train association relationship implied by AFC data,an alternative set of passenger spatial-temporal trajectories is constructed;then,a passenger spatial-temporal trajectory identification algorithm based on cluster analysis and Bayes’ theorem is proposed for different types of passengers respectively;the reliability of the algorithm is verified by the stability of passenger path selection between the same OD in normal operation;finally,the impact of actual emergencies on passenger flow distribution is analyzed.The case results show that the algorithm is reliable,and that emergencies will cause passenger congestion and passenger flow demand fluctuations,so it is necessary to take scientific prevention and control measures.(2)Network vulnerability assessment for emergencies.The impact mechanism of emergencies is complex,and the existing research lacks consideration of the systematic characteristics of urban rail transit.In order to identify the key aspects of the rail transit network system and improve the scientific nature of prevention and control plans,a network vulnerability assessment method is proposed.Firstly,the concept of vulnerability is defined and vulnerability assessment indicators are proposed on the basis of passenger behavior modeling;then,considering passenger behavior and line wiring settings,the vulnerability indicator calculation methods are proposed for three typical contingency scenarios such as section delay,train rescue and section disruption respectively.Finally,in order to investigate the risk resistance capacity of the network system under extreme conditions,a study is conducted on the scenario of simultaneous disruption of multiple sections,and a search algorithm based on "dominant sections" is designed to solve the problem of the huge number of section combinations and the difficulty in index calculation.The results show that the redundancy of line capacity and the setting of wiring settings are closely related to the system’s risk resistance capacity;in the face of extreme conditions,the simultaneous disruption of only 3% of key sections may cause 80% of the network’s passenger flow loss.(3)Collaborative operation management for emergencies.The real-time management and control of emergencies requires the cooperation of multiple systems,and the existing research lacks consideration of the control measures synergy and the uncertainty of passenger flow demand.In order to optimize the real-time management and control of emergencies,first analyze the problems of traffic adjustment and passenger flow control under emergencies,and explain the necessity and feasibility of collaborative operation management from the supply and demand sides of transport.Subsequently,a bi-level model is established for the collaborative optimization of traffic adjustment and passenger flow control,with the upper-level traffic adjustment model aiming at minimizing train delays and the lower-level passenger flow control model aiming at maximizing passenger flow on board;a robust optimization method was proposed for the uncertainty of passenger flow demand under emergencies.The solution algorithm based on sensitivity analysis is designed by combining the characteristics of the model;finally,an example analysis is conducted with a metro line of Beijing Subway.The results show that the collaborative operation management can improve the efficiency of train operation and passenger collection and distribution under the condition of ensuring passenger equity;compared with non-robust optimization,the robust optimized passenger flow control measures can deal with 15% passenger flow fluctuation at a cost of 4.16% passenger flow loss.Focusing on the theme of emergency prevention and control,this paper studies three key technologies: post-event evaluation and analysis,pre-event evaluation and prevention,and in-event management and control response,so as to provide theoretical and technical support for urban rail transit emergency prevention and control.