Visual analysis of bus flow based on grid clustering

Abstract

In recent years, the research of data visualization has attracted more and more attention, especially the visualization of traffic flow data. This paper proposes a grid clustering method based on k-means. First, the geographic data is divided into grid matrix, and then K-means is used to perform cluster analysis on the data. The traffic flow data is then displayed. In this paper, the inner feeling of public transport flow analysis is very important for public transport operation decision making, and provides a very important basis for the operation safety supervision and risk assessment decision of urban public transport.