Urban rail transit emergency passenger flow space-time distribution prediction method

Abstract

The invention provides an urban rail transit emergency passenger flow space-time distribution prediction method, which comprises the steps of analyzing historical emergency driving organization adjustment measures based on historical data, and mining passenger flow space-time distribution rules, influence ranges and passenger selection behaviors of historical emergencies; based on the AFC real-time card swiping data, predicting OD distribution under emergencies by using a space-time correlation prediction model in combination with a mining result of historical data; performing real-time adjustment and deduction on the train timetable under the emergency according to an analysis result of historical emergency driving organization adjustment measures, and updating an effective path of the track; and realizing rail transit passenger flow space-time distribution state prediction under different emergency scenes by combining the rail effective path updating result and the OD distribution prediction result under the emergency and based on a multipath probability distribution model. According to the method, the passenger flow distribution condition of the rail transit road network under the emergency situation can be accurately mastered in real time.

Description

technical field [0001] The invention relates to the technical field of urban rail transit emergency management, in particular to a method for predicting the temporal and spatial distribution of passenger flow in urban rail transit emergencies. Background technique [0002] In the case of urban rail transit network operation, the network structure is becoming more and more complex, the degree of correlation between each line is getting higher and higher, the types of emergencies are gradually diversifying, the frequency of occurrence is increasing, and the scope of spread is expanding. There will be a chain reaction, which is undoubtedly a severe test for the urban rail transit system that was originally operating at full capacity. Emergencies will affect the normal operation of all trains on the rail line. paralysis. [0003] At present, the Beijing rail transit real-time passenger flow monitoring system has been able to grasp the passenger flow status in the rail transit n...

AI Technical Summary

Problems solved by technology

[0013] The technical problem to be solved by the present invention is to provide a method for predicting the temporal and spatial distribution of passenger flow in urban rail transit emergencies, which can be used to mine historical The spatio-temporal distribution of passenger flow, the scope of influence, and passenger selection behavior of emergencies, and then use AFC real-time data and survey data to predict the distribution of rail transit OD passenger flow under emergencies, and then combine the deduction of train timetables to realize emergency response in emergencies. Passenger flow distribution, and finally get the passenger flow distribution indicators in the case of emergencies, such as the inbound and outbound volume and transfer volume of each station in the network, the passenger flow of time-sharing sections in intervals and the full load rate of intervals, and the passenger traffic volume of time-sharing lines in different directions , swap-in, line-in, and swap-out, and finally solve the problem of poor applicability of existing passenger flow forecasting models in emergencies

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