Optimization of Rail Transit Departure Frequency Based on Fuzzy Clustering - Take Shanghai Rail Transit Line 9 for Example

摘要

This article takes example of Shanghai Rail Transit Line 9, and uses fuzzy clustering method to classify passenger flow in different periods of the working and non-working days by MATLAB program. Full-day time intervals are divided into five categories, and we optimize the departure frequency based on the five categories. This optimization method improves the operational efficiency of urban railway transport, and reduces the cost of it. The method of research is innovative, and research findings are instructive in practice.