Analysis of Bus Line Passenger Flow Based on Big Data—A Case Study of Guangzhou Bus Line

Abstract

The passenger flow analysis which is based on the public transport passenger travel data could provide an important reference for the urban transit network planning and layout optimization. 8,926,605 smart card records of Guangzhou bus lines from August to December in 2014 and weather data have already been collected. Ali cloud computing technology is used to process the big data and analyze passenger flow characteristics. The test between Ali cloud computing technology and traditional SQL database technology has been made. K-means algorithm is utilized to cluster the passenger travel frequency, and the structure of the passenger travel type is gained. The results show that the seasonal weather have some influence on passenger flow each month, and the group of older residents is higher than the group of students in travel frequency. The travel frequency of passengers in low level accounts for more than 80%. Cloud computing technology is used to deal with the such big data, which has a good adaptability.