A passenger flow prediction method for urban rail transit under emergencies

Abstract

The invention discloses a method for predicting urban rail transit passenger flow under emergencies. The method includes: S1: Obtaining urban rail transit physical network information, train operation information, passenger flow data and emergency event information, and determining urban rail transit passenger flow distribution. and affected passenger flow data; S2: Construct a set of alternative travel plans for passengers under emergencies, and update the affected passenger flow data after passengers choose each alternative travel plan; S3: Comprehensive unaffected passenger flow data, calculate the The passenger flow of the station; this invention fully considers the impact of emergencies on urban rail transit operations, considers the characteristics of passenger travel behavior under emergencies, improves the accuracy of urban rail transit passenger flow distribution prediction under emergencies, and provides an effective basis for formulating effective Emergency plans and operation management measures provide theoretical basis, which can effectively divert passengers stranded due to emergencies, ensure passenger travel safety, and improve the service level of the subway operation department.

Description

Technical field [0001] The present invention relates to the technical field of urban rail transit. More particularly, to urban rail transit passenger flow forecasting method under one kind of emergencies. Background technique [0002] With the rapid social and economic development, urban rail transportation for its large capacity, high efficiency, low energy consumption, command and controllability, and other characteristics has become an important way of big city traffic travel. In recent years, the rapid development of my country's urban rail transit, which in some big cities such as Beijing, Shanghai, Guangzhou and other rail transit network has entered into the operational phase. In the context into network operation, urban rail transit passenger traffic continued to increase. Due to urban rail transit traffic has large, complex network structure characteristics, into a network under conditions event of emergencies, due to the lack of effective passenger flow forecasting, ope...

AI Technical Summary

Problems solved by technology

Existing rail transit passenger flow forecasting methods roughly handle passenger travel choices under emergencies, fail to fully consider the diversity and possibility of travel plans, and fail to effectively predict passenger flow based on actual needs

Images