Contribution to Real-time Control of Safety and Boarding Flows Using Dynamic Queue Models

Passenger flow management in airports constitutes today a major operational challenge, amplified by the sustained growth of global air traffic, the diversification of traveler profiles, and the continuous strengthening of regulatory requirements in terms of safety and security. Control points, particularly those related to safety inspections, check-in formalities, and boarding procedures, represent critical areas where congestion phenomena can quickly appear and disrupt the entire operational chain. These disruptions impact not only the quality of service offered to passengers but also flight punctuality and the overall performance of airport infrastructure. Traditional planning approaches, often static and based on average forecasts, show their limits in the face of the temporal variability of passenger flows and the unpredictability of disruptive events such as delays, seasonal peaks, or operational incidents. In this context, this article proposes an in-depth analysis of the contribution of dynamic queue models in passenger flow management. These models better represent the real behaviors of airport systems by integrating real-time fluctuations and interactions between different service points. The study highlights the ability of these approaches to anticipate congestions, optimize the allocation of human and material resources, and significantly improve the fluidity of safety and boarding processes. The results obtained demonstrate that the integration of these analytical tools constitutes a strategic lever to strengthen operational efficiency, improve the passenger experience, and increase the resilience of airports to traffic variations and uncertainties in the air transport system.