The Study of Network Connectivity and Traffic Impact Based on Random Walk Algorithm and Monte Carlo Simulation

This study analyzes the impacts on connectivity, stability, and traffic flow in urban transportation networks when critical infrastructure fails, using Random Walk algorithms and Monte Carlo simulations. First, a transportation network model is constructed using the Random Walk algorithm, and the connectivity of the traffic system is calculated. Through interference simulations, the impact of node or edge removal on the connectivity of the transportation network is assessed. The results show that while the loss of critical infrastructure leads to a decrease in network connectivity, the overall impact is limited. However, the stability of the transportation network is significantly reduced in the absence of infrastructure. Next, based on Monte Carlo simulations, a quantitative analysis of the impact of missing roads on traffic flow is conducted. The results indicate that the removal of certain roads, particularly key arterials, significantly affects the overall traffic flow, creating greater pressure on the network. Through comprehensive analysis, this study provides a quantitative evaluation method for the resilience and emergency management of urban transportation systems, offering both theoretical value and practical applications.