Passenger congestion alleviation in large hub airport ground-access system based on queueing theory

Airport public transport systems are plagued by passenger queue congestion, imposing a substandard travel experience and unexpected delays. To address this issue, paper proposes bi-level programming for optimizing queueing network in airport access based on choice behavior. For purpose, we derive system, which include the taxi, bus, subway. Then, propose model network. The lower level subprogram is designed to correspond profit maximization principle mode behavior, while upper minimize maximum number of passengers waiting be served. Decision makers consider tolls incentivize them change their achieve goal avoiding congestion. Finally, develop successive weighted averages (MSWA) method solve subprogram's share rates ant lion optimization (ALO) program's toll scheme upper-level objectives. We prove effectiveness proposed two situations simulation, daytime evening cases. numerical results highlight that our strategy can alleviate congestion both scenarios effectively improve evacuation efficiency.