Multi-mode public transport passenger flow calculation method based on big data technology

Abstract

The invention belongs to the technical field of intelligent transportation, and particularly relates to a multi-mode public transport passenger flow calculation method based on a big data technology.According to the method, the subway IC card data is combined on the basis of the bus IC cards and the GPS data, the fusion analysis is carried out on the bus travel passenger flow under multiple modes, a derivation method of a get-off point is optimized, a new idea of matching the get-off point based on travel characteristics is provided, and the sample expansion is carried out on a result by considering multiple factors. The method provided by the invention can more accurately derive the passenger flow OD distribution condition of multi-mode bus travel, is more suitable for the traffic environment in which the bus and subway combined public transport travel modes are gradually universal at present, and can provide help for the planning and optimization of the public transport industry.

Description

technical field [0001] The invention belongs to the technical field of intelligent transportation, and in particular relates to a multi-mode bus passenger flow estimation method based on big data technology. Background technique [0002] Public transportation has the characteristics of low road occupancy rate, large transportation volume, green and efficient, and has inherent advantages in reducing urban congestion and improving the environment. Many large cities have established urban intelligent public transport systems, and there are massive amounts of data stored in urban intelligent transportation systems that can be used to calculate passenger flow. [0003] In the prior art, the patent "A method for calculating the OD of bus passengers based on intelligent bus system data (application number 201610229224.9)" discloses a method for estimating the OD of bus passengers based on intelligent bus system data. source, analyze the travel time and space characteristics of bus...

AI Technical Summary

Problems solved by technology

[0004] (1) Only the passenger flow estimation under the single travel mode of the bus has been studied, and how to mine the multi-source data combined with the bus and subway has not been considered, and how to derive the passenger flow of the corresponding multi-mode integrated public transportation system;

[0005] (2) The judgment method of the alighting point and the OD matrix expansion method are not comprehensive in consideration of the factors. The judgment of the alighting point is only analyzed for the general situation, ignoring the sporadic traffic trips, and the success rate of the calculation needs to be improved; the expansion of the OD matrix In the sample, only the expansion of the data with unsuccessful matching is considered, and the situation of non-swipe card travel is not considered, which is inconsistent with the actual situation

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