Urban rail transit passenger flow analysis method based on AFC (Automatic Fare Collection) passenger ticket data

Abstract

The invention provides an urban rail transit passenger flow analysis method based on AFC (Automatic Fare Collection) passenger ticket data. The method comprises the following steps: on the basis of historic passenger ticket data of an urban rail transit AFC system, systematically analyzing spatial and temporal distribution character of the urban rail transit passenger flow on the aspects of three levels such as stations, routes / intervals and road networks in combination with an urban rail transit network and an actual train working diagram; and meanwhile, providing a two-dimension / three-dimension visualization technology and a reappear technology of process evolution for the passenger flow spatial and temporal distribution. The method provided by the invention has the relatively good advancement, practicability and universality, the spatial and temporal distribution character of the urban rail transit network passenger flow can be comprehensively mastered from different levels systematically by using the method so as to provide good scientific data and support evidence for the operation management and organization optimization of the urban rail transit, and provide efficient technological approaches for reappearing the spatial and temporal distribution evolution process and researching the passenger flow evolution rule of the urban rail transit network passenger flow.

Description

technical field [0001] The invention relates to the technical field of intelligent data mining, in particular to an analysis method for urban rail transit passenger flow based on AFC passenger ticket data. Background technique [0002] Urban rail transit (Rail Transit, hereinafter referred to as: ATS) has the characteristics of large capacity, fast speed, safety, punctuality, environmental protection, energy saving and land use, and is the backbone system of the urban public transportation system. According to statistics from the China Urban Rail Transit Association, by the end of 2013, 87 urban rail transit lines had been built and put into operation in 19 cities in my country, with an operating mileage of 2,539km. The rail transit in cities such as Beijing, Shanghai, and Guangzhou has gradually developed from a single-line operation and a skeleton network to a networked state. The accessibility of passengers and the attractiveness of rail transit have been greatly improved...

AI Technical Summary

Problems solved by technology

[0005] In general, the existing passenger flow analysis system / passenger flow analysis work of urban rail transit lacks systematicness, dynamicity and microscopicity, which are mainly reflected in: (1) The comparative analysis of passenger flow is mainly the comparative analysis of the longitudinal time dimension of the same object, and there is a lack of similar objects (2) The time distribution characteristics and evolution law of passenger flow OD on the urban rail transit network are not analyzed in depth; (3) Passenger flow paths are generally allocated based on the impedance of the K short circuit, and the urban rail transit network and actual trains are not combined. Operation diagrams to accurately determine passenger travel routes and train numbers; (4) There is no analysis of the passenger capacity / crowding degree of trains in different sections and the change of passenger flow in different sections of sections

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