Evaluating the robustness of attributed dynamic bus-metro networks based on community reconstruction

Despite significant advances in applying complex network theory to analyze the robustness of public transport systems, one still cannot seamlessly incorporate complex topological structures into existing algorithms, network modelling remains inaccurate, and high-level features of public transport systems cannot be captured effectively. Moreover, the identification of community structures with dynamic transfer relationships between bus and metro systems requires well-designed formulas and sophisticated computer codes. This study aims to evaluate the robustness of bus-metro networks based on community reconstruction. Firstly, we constructed an attributed dynamic bus-metro network, considering the socio-economic environment of the public transport system and the dynamic transfer relationship between bus stops and metro stations. Secondly, we introduced the community reconstruction approach, proposed a robustness estimation model, and designed community-based strategies for node and edge attacks, which are ComNA and ComEA, respectively. Finally, taking a real-world bus-metro system in Xi'an as a case study, this research evaluates the system's robustness under various attack strategies and analyzes the impact of dynamic transfer relationships on robustness. The results reveal that: (1) The performance of public transport networks exhibits varying trends under different attack strategies. Notably, the bus-metro network demonstrates enhanced robustness to random attacks compared to targeted attacks. (2) Community-based attack strategies are more effective than traditional methods in dismantling public transport networks. (3) Enhancing the transfer capacity at metro stations significantly improves the overall robustness of public transport systems. These results are of critical importance for improving the robustness of public transport systems.