Passenger flow comprehensive prediction system and prediction method

Abstract

The invention relates to a passenger flow comprehensive prediction system and method, and the system comprises: a short-time passenger flow prediction subsystem which is used for generating short-timepassenger flow prediction; a conventional short-term passenger flow prediction subsystem which is used for predicting OD quantity among rail transit line websites in days, weeks, months, years and holidays and quickly realizing distribution of the predicted OD quantity in the whole network; and a predictable large passenger flow prediction subsystem which is used for predicting the OD quantity between rail transit line websites under a large passenger flow event and quickly realizing the distribution of the predicted OD quantity in the whole network. According to the passenger flow predictionmethod, passenger flow distribution in special time periods such as short-term passenger flow distribution, conventional short-term passenger flow distribution and holidays is predicted to sort passenger flow, so that excessive congestion caused by mismatching of supply and demands is avoided, and the situations of transport safety reduction and transport capacity waste are avoided.

Description

technical field

[0001] The invention relates to the field of passenger flow forecasting, in particular to a passenger flow comprehensive forecasting system and a forecasting method. Background technique

[0002] At present, the passenger volume of urban rail transit continues to increase, and the intensity of passenger flow increases steadily. As a large number of subway lines are built and put into operation in major cities, the problems of line management and scheduling have become increasingly prominent. For example, the supply and demand of line trains during the morning and evening peak hours do not match, resulting in overcrowding and overcrowding of trains, which reduces the safety of transportation; and the low load rate of vehicles in peak and low peaks leads to waste of transport capacity. Therefore, there is a need for a method that can effectively predict short-term passenger flow distribution, regular short-term passenger flow distribution, and special period pa...

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