A Passenger Flow Prediction Method for the Opening of New Urban Rail Transit Lines Based on Historical Data

Abstract

The invention discloses a rail transit new line opening passenger flow prediction method based on historical data. The method comprises the following steps: carrying out clustering analysis to the historical entering and exiting station amount data of an existing station, extracting station attribute, and obtaining a relationship model between the station attribute and entering and exiting station amount; on the basis of the station attribute of a new line station and the relationship model, predicting the hourly entering and exiting station amount of the new line station; on the basis of a regression model created on the basis of the historical OD (Origin Destination) distribution data training learning of the existing station, obtaining the OD distribution ratio of the station which needs to be predicted; and according to the relative position and the spatial distance of the line, determining an affected station area of the existing line after the new line is opened, obtaining the induced passenger flow volume of the affected station on the basis of an increment basic formula and travel time, and determining the transfer passenger flow volume of the affected station on the basis of bus feeder line amounts and distance between two stations.

Description

technical field [0001] The invention relates to the technical field of intelligent transportation, in particular to a method for predicting the passenger flow of new lines of urban rail transit based on historical data. Background technique [0002] In order to meet people's ever-increasing transportation needs, the urban rail network is constantly expanding. The construction of a large number of new lines and the emergence of interchange stations have changed the original topology of urban rail transit, and the connectivity and accessibility of urban rail network have changed, thus affecting the travel choice behavior of travelers. Passenger flow on the urban rail network The distribution changes accordingly. Therefore, before the opening of the new line, combined with the operating conditions of the new line and the current operating status of the existing line network, forecasting the passenger flow of the opening of the new line and the impact on the passenger flow of t...

AI Technical Summary

Problems solved by technology

[0004] However, using the above method requires a large number of surveys to obtain data, which is difficult to collect and takes a long time to collect. In addition, the passenger flow is only predicted according to the characteristics of the new site itself in the model construction, and the prediction accuracy is low.

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