The Systematic Processing Method and Application of Big Data of Bus System in Small and Medium-Sized Cities Based on One Ticket System

In order to analyze the travel characteristics of bus passengers, this paper uses the IC card data, the bus GPS data, the on-board machine data and the one-way station relationship table, and puts forward a systematic processing method for the big data of the one-ticket bus system through the association and fusion of various data. The analysis database was built based on Oracle, and the code was written in Python language. Four kinds of station inference algorithms, namely passenger boarding station inference algorithm, passenger alighting station inference algorithm based on travel chain, passenger alighting station inference algorithm based on probability and passenger transfer station identification algorithm, were constructed. Based on this, Jiaozuo’s bus big data is used to identify passenger flow distribution points and passenger flow corridors, so as to obtain the distribution of passenger flow on and off bus stops, passenger flow on bus lines and transfer passenger flow at bus stops. It effectively improves the accuracy of time matching, and can completely identify a day’s bus travel information of passengers. It is universal to calculate bus passenger loading and unloading stations in small and medium-sized cities with sparse GPS data.