Short-time passenger flow prediction method for new line station of urban rail transit

Abstract

The invention relates to a short-time passenger flow prediction method for a new line station of urban rail transit , which comprises the steps of S1, cleaning and preprocessing station data, passenger flow data and POI data required by a prediction model, and dividing passenger flow into different stages after a new line is opened; S2, on the basis of the POI data cleaned in the S1, clustering point land use functions of the whole website by taking the land use scale around the new line station as coordinates; S2, constructing a new line station historical passenger flow database by combining the existing stations of which the clustering results are consistent with the new line station with the real-time new line passenger flow data obtained in the step S1; S3, based on S2, creating the historical passenger flow database for the new line station; S4, converting the short-time passenger flow volume into a passenger flow time-sharing coefficient based on the passenger flow data obtained in S2; and S5, combining the all-day passenger flow data in the S3 with the passenger flow time-sharing coefficient in the S4 to obtain a short-time passenger flow prediction value result of the new line station. According to the invention, the passenger flow prediction precision is improved, and the service level of urban rail operation is improved.

Description

technical field [0001] The invention relates to a method for predicting short-term passenger flow at a station of a new urban rail transit line, which belongs to the technical field of urban rail transit. Background technique [0002] With the development of society and economy, the urban population is increasing day by day, the scale and scope of the city are expanding, and the travel demand and travel distance of residents are also increasing sharply. In order to meet the travel needs of residents, many large cities are using large-capacity, long-distance, and efficient rail transit as the backbone system for residents' bus travel. With the extension of new lines and the opening of new stations, urban rail transit has entered the stage of networked operation, and the links between lines have become closer. The adjustment of cable network transportation organization is particularly critical. [0003] In the actual operation process, after the opening of the new line stati...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to overcome the problems existing in the prior art, provide a short-term passenger flow prediction method for urban rail transit new line sites, strengthen the extraction of effective features of historical data, to further enhance the robustness of the prediction model, improve Accuracy of short-term passenger flow forecasting. Aiming at the problem of insufficient granularity of passenger flow forecasting by the four-stage method adopted in the feasibility study stage of new line workers, short-term passenger flow forecasting is carried out to subdivide the forecasting granularity, providing passenger flow for scientific operation and refined management of urban rail operating companies data base

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