Method for predicting bus connection scale of rail transit station influenced by large passenger flow

Abstract

A method for predicting bus connection scale of a rail transit station influenced by large passenger flow comprises the steps: carrying out rail transit and connection bus passenger flow characteristic analysis, including rail transit passenger flow data, bus passenger flow data connected with rail transit stations and rail transit and bus travel characteristics; determining historical rail transit station distributed passenger flow variation influenced by large-scale activities; predicting the passenger flow average variation of the rail transit station caused by the influence of the (k + 1)th large-scale activity; predicting the connection passenger flow variation of the ith bus line connected with the rail transit station; and determining the number of times of newly increased bus transfer of the bus route influenced by large-scale activities. According to the method, the big data technology is adopted, the rail transit connection passenger flow variation caused by large-scale activities is accurately analyzed and predicted, and accurate dispatching of buses connected with rail transit stations is achieved. The service level of the bus is greatly improved, and effective transfer between rail transit and the bus is improved, and the newly-added traffic requirement caused by large-scale activities is greatly met.

Description

technical field [0001] The invention relates to a method for predicting bus connection scale. In particular, it involves a method for predicting the scale of bus connections at rail transit stations affected by large passenger flows. Background technique [0002] In recent years, with the strengthening of my country's opening to the outside world and the improvement of people's living standards, major cities in China have held various large-scale activities such as performances, exhibitions, and sports events. The holding of large-scale events has triggered a large number of concentrated travel of people, which has brought enormous pressure to the already tense urban transportation system. The holding of large-scale events in the city will form a high-intensity and high-density gathering or dissipating passenger flow in a short period of time, which brings great challenges to the efficient operation of the urban transportation system. As a mass transportation mode, rail tr...

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Problems solved by technology

[0003] For example, within a relatively short period of time before and after large-scale events in the city, some rail transit stations will form an obvious phenomenon of large passenger flow, and there will be insufficient number of connecting buses, which will affect the service level of connecting buses and the experience of residents

[0004] At present, the existing methods for predicting the size of conventional bus connection stops in this technical field at home and abroad are not comprehensive enough. With the wide application of conventional bus and rail transit data collection and big data technology, it can be combined with big data analysis to effectively solve the problem of bus connection. Unreasonable Problems in Predicting the Size of Trains

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