Research on Flexible Public Transportation Planning Based on Node Importance Clustering

As a new public transport operation mode, the flexible transit system integrates the high efficiency and low cost of conventional public transportation with the flexibility of demand-responsive public transportation. At present, it has been successfully employed in many foreign cities. The operation results show that flexible public transportation is an effective way to solve the problem of public transport service in low travel demand density zones. This paper first analyzes five factors that affect the planning of flexible public transportation stops, and constructs a node importance model based on these five factors, using K-means clustering algorithm to determine the nodes suitable for planning bus stops. The results show that the method is feasible and practical, and can provide a theoretical basis for domestic enterprises to plan flexible public transportation.