Research on the optimization of public transportation networks: the big data and NetworkX framework
Qi Xu, Jiahao Wang, Jie Huang, Hailun Deng, Xiang Wang, Qianhong Wu · 2025
As urbanization accelerates and populations grow, urban public transportation systems face unprecedented challenges. As a tourist and transportation hub city, Guilin experiences significant fluctuations in travel demand, and traditional scheduling and planning methods are no longer sufficient to meet the complex and dynamic transportation needs. By leveraging transportation big data and intelligent analysis technologies, this study utilized the NetworkX framework to construct a public transportation network model for Guilin City, and conducted a systematic analysis of network topology characteristics and data mining. By integrating multi-source data such as bus GPS trajectories, passenger card swipe records, and road traffic flow, data quality and consistency were ensured to achieve precise modeling. Based on the definition of node and edge attributes, this study conducted an in-depth analysis of key indicators such as node centrality, connectivity, shortest paths, and community structure, revealing the potential patterns and bottlenecks of the transportation network. At the same time, clustering analysis, association rule mining, and predictive modeling techniques were used to identify passenger travel patterns and transfer characteristics, and to detect potential abnormal behaviors. The research results indicate that complex network analysis can effectively identify system weaknesses and potential congestion risks, providing scientific basis for public transportation route optimization, transfer system design, and resource allocation. Through experimental verification and visualization analysis, this method demonstrates significant advantages in improving traffic operation efficiency, enhancing passenger experience, and promoting sustainable development, laying a solid foundation for the construction of an intelligent, efficient, green, and low-carbon urban transportation system.