2012Advanced engineering forumOpen access

Passengers Flow Forecasting Model of Urban Rail Transit Based on the Macro-Factors

Bin Shang, Xiao Ning Zhang

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Abstract

In China, many cities are planning urban rail transit system, but a comprehensive passenger flow estimation model is still lacking. The total passenger flow of urban rail transit in a city depends on many factors, such as urban population, total length of rail lines, gross domestic production of the city etc. To estimate the total passenger flow of urban rail transit, a linear regression model with multiple variables is established in the paper, based on the real data collected in many cities with urban rail transit operating. The comparison of the estimated flow and the real flow in many cities shows that the model is very accurate in passenger flow forecasting.

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In China, many cities are planning urban rail transit system, but a comprehensive passenger flow estimation model is still lacking. The total passenger flow of urban rail transit in a city depends on many factors, such as urban population, total length of rail lines, gross domestic production of the city etc. To estimate the total passenger flow of urban rail transit, a linear regression model with multiple variables is established in the paper, based on the real data collected in many cities with urban rail transit operating. The comparison of the estimated flow and the real flow in many cities shows that the model is very accurate in passenger flow forecasting.

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Available abstract

In China, many cities are planning urban rail transit system, but a comprehensive passenger flow estimation model is still lacking. The total passenger flow of urban rail transit in a city depends on many factors, such as urban population, total length of rail lines, gross domestic production of the city etc. To estimate the total passenger flow of urban rail transit, a linear regression model with multiple variables is established in the paper, based on the real data collected in many cities with urban rail transit operating. The comparison of the estimated flow and the real flow in many cities shows that the model is very accurate in passenger flow forecasting.

Key concepts: Urban rail transit, Transport engineering, Macro, Flow (mathematics), Transit (satellite), China, Population, Estimation

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