Bus passenger travel station prediction method, storage medium and server

Abstract

The invention discloses a bus passenger travel station prediction method, a storage medium and a server. The bus passenger travel station prediction method comprises the steps that bus GPS track data,passenger bus IC card swiping record data and bus station and route vector data of a certain urban area are acquired; based on the bus GPS track data, the passenger bus IC card swiping record data and the bus station and route vector data, historical bus card swiping get-on stations of passengers are matched, and passenger historical get-on station travel links are constructed; spatial clusteringis carried out on the bus stations, and a passenger historical get-on clustering travel link is constructed; bus get-on clustering is predicated based on a variable-order Markov model and the passenger historical get-on clustering travel link, and a specific get-on station is predicated based on a probability model and based on the analysis of the bus and subway mixed travel chain, bus get-off clusters and get-off stations are predicated. According to the method, the bus get-on and get-off stations are well predicted, and the prediction accuracy of the travel stations is obviously improved.

Description

technical field [0001] The invention relates to the field of spatial information applications, in particular to a method for predicting bus passenger trip sites, a storage medium and a server. Background technique [0002] With the popularization of intelligent public transportation systems, intelligent transportation IC cards are widely used in public transportation fare payment systems, which record a large amount of travel trajectory information of users. Accurately predicting the bus stop information of urban residents can greatly reduce the financial expenditure of government traffic surveys, maximize the profits of related companies, and help to grasp the changes in bus passenger flow, assist bus operation decisions and optimize bus routes. It also provides new perspectives in many fields such as characteristics of group public transportation travel behavior, estimation of urban traffic flow, analysis of urban spatial structure and functional adaptability. [0003] No...

AI Technical Summary

Problems solved by technology

[0006] In view of the above-mentioned deficiencies in the prior art, the object of the present invention is to provide a method for predicting bus passenger travel sites, st

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