Rail transfer station passenger flow jam risk assessment method based on AFC (automatic fare collection) card swiping data

Abstract

The invention discloses a rail transfer station passenger flow jam risk assessment method based on AFC (automatic fare collection) card swiping data. The method includes the steps: preprocessing AFC original transaction data; assessing rail transfer station passenger flow jam based on the AFC card swiping data; extracting, removing and screening AFC original card swiping data and recognizing transfer passenger flow based on database analysis and data mining technology; acquiring arrival, departure and transfer passenger flow of a transfer station at different time intervals based on the AFC card swiping data, and manually measuring physical parameters at typical positions in the transfer stations on site; building passenger flow saturation assessment indexes at the typical positions to comprehensively assess passenger flow demand and supply relations at the positions; calibrating model parameters according to index maximum values serving as input values of a model in assessment time intervals; calculating the weight of saturation indexes of different typical positions in the model according to an entropy weight method, clustering risk assessment and dividing rail transfer station passenger flow jam five-level risk grades.

Description

technical field [0001] The invention relates to a risk assessment method for passenger flow congestion at a rail transfer station based on AFC card swiping data, and belongs to the field of public transportation data mining application and service evaluation. Background technique [0002] With the development of public transportation, the rail network of major cities is becoming more and more perfect, the substantial increase in rail passenger traffic, the increasing commuting distance of residents and the continuous increase in the number of rail transfers have gradually increased the passenger pressure on rail transfer stations, especially in During the morning and evening peaks of working days and major holidays, how to realize the passenger flow monitoring inside the rail transfer station and how to realize the quantification and classification of the passenger flow congestion risk in the rail transfer station at the micro level have become important issues that affect th...

AI Technical Summary

Problems solved by technology

However, the applicable object of this method is the rail network, and it cannot realize the calculation and analysis of the internal passenger flow of rail transfer stations.

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