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, this paper proposes a bi-level programming for optimizing queueing network in airport access. Firstly, we derive queueing network for airport public transport system, which include the taxi, bus, and subway. Then, we propose a bi-level programming model for optimizing queueing network. The lower level subprogram is designed to solve the passenger transport mode choice, while the upper level subprogram is designed to minimize the number of passengers waiting to be served with queue tolls. Finally, we develop the successive weighted averages (MSWA) method to solve the lower subprogram's passenger share rates and the ant lion optimization (ALO) method to solve the bi-level program's queue toll scheme. The simulation results highlight that our strategy can alleviate queue congestion for daytime and evening scenarios and effectively improve evacuation efficiency.

Automated summary

This paper proposes a bi-level programming model to optimize the queueing network in airport access, which can alleviate queue congestion and improve passenger evacuation efficiency in airport public transport systems.