2020Journal of Physics Conference SeriesOpen access

Research on Passenger Flow Control Model of Urban Rail Transit Network

Xue Su, Yiping Li

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Abstract

Abstract The current urban rail transit faces the pressure of effective transportation management brought about by the large passenger flow. Through this research, it is proposed to construct a coordinated control model for urban rail transit passenger flow and optimize the urban rail transit operation organization. Using the Mixed Logit model to construct the urban rail transit network passenger flow collaborative control optimization model can accurately describe the distribution of the urban rail transit network passenger flow online, which is especially applicable to the network topology change scenario brought by the new line introduction. Empirical evidence shows the correctness and effectiveness of the model.

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Abstract The current urban rail transit faces the pressure of effective transportation management brought about by the large passenger flow. Through this research, it is proposed to construct a coordinated control model for urban rail transit passenger flow and optimize the urban rail transit operation organization. Using the Mixed Logit model to construct the urban rail transit network passenger flow collaborative control optimization model can accurately describe the distribution of the urban rail transit network passenger flow online, which is especially applicable to the network topology change scenario brought by the new line introduction. Empirical evidence shows the correctness and effectiveness of the model.

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Available abstract

Abstract The current urban rail transit faces the pressure of effective transportation management brought about by the large passenger flow. Through this research, it is proposed to construct a coordinated control model for urban rail transit passenger flow and optimize the urban rail transit operation organization. Using the Mixed Logit model to construct the urban rail transit network passenger flow collaborative control optimization model can accurately describe the distribution of the urban rail transit network passenger flow online, which is especially applicable to the network topology change scenario brought by the new line introduction. Empirical evidence shows the correctness and effectiveness of the model.

Key concepts: Urban rail transit, Transport engineering, Construct (python library), Correctness, Rail transit, Computer science, Twin cities, Transit (satellite)

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