Research on prevention and control strategies for passenger group events due to flight delays based on multi-agent modelling

• A dynamic evolutionary model for passenger group events is proposed, grounded in complex adaptive system theory. • Evolution trends of group behaviour are predicted and validated via real-world case studies and questionnaire surveys. • Specific strategies are evaluated to provide actionable insights for emergency decision-making in aviation management. • An agent-based simulation offers a novel perspective on group opinion and behavior evolution during flight delays. With the rapid growth of the civil aviation industry, the frequency of flight delays has significantly increased. The severe consequences of passenger group events during flight delays are becoming increasingly prominent. This study employs a multi-agent modeling and simulation methodology to construct a dynamic evolutionary model of passenger group events. NetLogo software is employed to simulate dynamic interactions among passengers, airports, airlines, and key figures across various scenarios. Results indicate that parameter variations and stakeholder behaviors significantly influence passenger opinions. Consequently, four prevention and control strategies are proposed based on key influencing factors and simulation outcomes. Additionally, simulation experiments are conducted to evaluate the effectiveness of these strategies, identifying optimal combinations for airports and airlines across varying stages of evolution and development scenarios, thereby offering valuable guidance for emergency decision-making.