Railway station passenger flow and connection mode prediction method based on overall cooperation
A railway and passenger flow technology, which is applied in the field of prediction of passenger flow and connection mode of railway stations based on overall coordination, can solve problems such as independent operations, and achieve high precision results
Inactive Publication Date: 2020-11-03
广州市交通规划研究院
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[0008] The purpose of the present invention is to overcome the deficiencies of the prior art, to provide a method for predicting passenger flow and connection mode at railway stations based on overall coordination, and to solve the problem of "each doing his own thing and doing his own thing" in the single-point prediction idea in the traditional railway station passenger flow prediction. point of view" flaw
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[0057] The present invention will be further described in detail below with reference to the drawings and specific embodiments. A method for predicting passenger flow and connection methods at railway stations based on overall coordination adopts a point-to-point forecasting idea. The overall travel volume is controlled by the city's total outbound travel forecast, and the passenger transport scale of each hub station is divided layer by layer. Such as figure 1 As shown, in order to make up for the limitations of single-point forecasting ideas and the shortcomings of global forecasting ideas that cannot be subdivided into single points, the present invention establishes a set of passenger flow and connection method prediction methods for railway stations based on overall coordination, which mainly include:
[0058] Use the elastic coefficient of economic growth and outbound travel growth to reasonably predict the scale of urban outbound travel, and avoid common trend analysis met...
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The invention provides a railway station passenger flow and connection mode prediction method based on overall collaboration. The method comprises the following steps: 1, predicting the total scale ofurban outward travel by using elastic coefficients of economic growth and outward travel growth; 2, predicting the railway passenger capacity scale; 3, performing spatial distribution prediction of the railway passenger flow sending based on the urban gravitation; 4, predicting the passenger flow volume of the railway according to different systems and different lines; 5, predicting population coverage and station passenger flow volume based on the accessibility of urban collection and distribution transportation; 6, predicting the connection mode and the connection facility scale of each hub. According to the method provided by the invention, the mutual relationship among various traffic modes, each hub and each line is comprehensively considered, the clarification function and the alignment positioning of each hub are facilitated, and a powerful support effect is achieved in the hub comprehensive development planning and decision-making work of a higher regional level.
Description
Technical field [0001] The present invention relates to the technical field of traffic flow prediction, in particular to a method for predicting passenger flow and connection modes of railway stations based on overall coordination. Background technique [0002] Railway stations are the most important and key link in a comprehensive urban transportation hub, and an important node connecting regional and urban transportation. They play an important role in improving the quality of comprehensive transportation and ensuring the quality and benefits of comprehensive transportation. Passenger flow forecasting is an important basis for supporting the construction of comprehensive transportation hubs. Reasonable passenger flow forecasting can timely grasp the development needs of the hub and correctly guide the future construction of the hub. [0003] To this end, it is necessary to formulate a complete scientific forecasting system for the research of passenger flow forecasting in hubs, a...
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IPC IPC(8): G06Q10/04G06Q50/26G06Q50/30
CPCG06Q10/04G06Q50/26G06Q50/30
Inventor 马小毅刘明敏宋程陈先龙金安丁晨滋张科刘新杰陈嘉超陈建均卢泰宇李磊艾冠韬
Owner 广州市交通规划研究院