A multi-mode bus passenger flow estimation method based on big data technology

Abstract

The invention belongs to the field of intelligent transportation technology, and specifically relates to a multi-mode bus passenger flow estimation method based on big data technology. The method described combines the bus IC card and GPS data with the subway IC card data, conducts a fusion analysis of the bus travel passenger flow in multiple modes, optimizes the derivation method of the alighting point, and proposes a method based on A new idea of ​​using travel characteristics to match drop-off points, and considering multiple factors to expand the results. The method of the present invention can more accurately deduce the passenger flow OD distribution of multi-mode bus travel, is more suitable for the traffic environment in which the bus + subway combined public transport travel mode is becoming more and more common, and can provide help for the planning and optimization of the public transportation 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

Images