Passenger going-out behavior analysis method based on subway card-swiping data

Abstract

The invention discloses a passenger going-out behavior analysis method based on subway card-swiping data. The passenger going-out behavior analysis method is characterized in that the subway going-out behaviors can be classified, and the classification results have the obvious and easy-to-observe characteristics, and can be widely used for the intelligent traffic passenger going-out behavior analysis. The passenger going-out behavior analysis method is characterized in that S1, data pre-processing can be carried out; original data can be merged and organized, and passenger going-out records can be acquired; every passenger going-out record comprises a passenger going-out entrance station, an entrance card-swiping time, an exit station, and an exit card-swiping time; S2, characteristics can be extracted; according to the passenger going-out records, the passenger entrance temporal clustering can be carried out to acquire the fixed going-out days of every passenger, and then the passenger going-out characteristics can be acquired after the extraction of the passenger going-out characteristics; S3, passengers can be clustered; the passenger clustering can be carried out according to the passenger going-out characteristics, and the passenger clustering result can be acquired and analyzed.

Description

technical field [0001] The invention belongs to the technical field of intelligent transportation, and in particular relates to a passenger travel behavior analysis method based on subway card swiping data. Background technique [0002] Today, with the accelerated development of industrialization and urbanization, millions of people are pouring into big cities, which brings huge pressure to urban management and urban traffic. As the backbone of urban transportation, rail transit can effectively alleviate traffic congestion and improve the efficiency of urban transportation. In foreign countries, rail transit has experienced hundreds of years of development, and it has been proven that it has played a pivotal role in urban development and has assumed a major share in public transportation. The research on the travel behavior of subway passengers is an important basis for rail transit research. Whether the existing data can be used to accurately analyze and grasp the rail tr...

AI Technical Summary

Problems solved by technology

Traditional rail travel behavior analysis models and methods that directly observe the flow of people and station throughput have been difficult to meet more accurate and refined needs

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