Urban rail transit section passenger flow speculation method based on train operation timetable

Abstract

The invention discloses an urban rail transit section passenger flow speculation method based on a train operation timetable. The method comprises steps of firstly selecting enough sample size of history departure transaction data from a rail transit history database so as to carry out data cleaning; then, by considering passenger flow conditions, extracting transaction data related to a target route in a net from the cleaned data; by use of history target route data, establishing a history passenger flow unidirectional OD (origin-destination) matrix; screening real-time data of the transaction day before the prediction period; by referring a counting step of the history passenger flow unidirectional OD matrix, acquiring a real-time passenger flow unidirectional OD matrix; and by combining reaching passenger flow data of a station, constructing a fracture surface passenger flow speculation model based on a BP neural network and detecting and adjusting the model. According to the invention, the method can be used for estimating and predicting section passenger flows of all regions of a rail transit line and data support is provided for operation state evaluation and operation optimization management of a rail transit enterprise.

Description

technical field [0001] The invention relates to a method for estimating passenger flow in urban rail transit sections based on train running timetables, which belongs to the intelligent technology of urban rail transit. Background technique [0002] Urban rail transit, as a mode of travel with multiple advantages such as fast, comfortable, reliable, and environmentally friendly, has received great attention in many large cities, especially in China, a city with a large population and high population density. With the strong support of local governments for rail transit construction and the gradual development and improvement of rail transit network, many cities in China have ushered in the stage of network operation. However, the operation and management of urban rail transit in my country is still in the early stage of development, with relatively insufficient management experience and lack of scientific theoretical guidance, and the level of operation and management needs ...

AI Technical Summary

Problems solved by technology

The simulation is actually a simulation of the changes in passenger flow distribution of the rail transit network for a period of time in the future. The simulation results are speculations based on the proposed plan and cannot directly reflect the passenger flow demand of the section.

In addition, it is difficult for passengers to transfer from other lines to the target line to be included in the cross-sectional passenger flow of the target line

Images