The complexity and resource-sharing nature of traffic within multi-airport regions present significant challenges for air traffic management. This paper aims to develop a mesoscopic traffic model for exploring the traffic dynamics under coupled operations, and thus to conduct capacity decoupling analysis. We propose an integrated surface–airspace model. In the surface model, we utilize linear regression and random forest regression to model unimpeded taxiing time and taxiway network delays due to sparsity of ground traffic. In the airspace model, a dualized queuing network topology is constructed including a runway system, where the $G(t)/GI/s(t)$ fluid queuing model is applied, and an inter-node traffic flow transmission mechanism is introduced to simulate airspace network traffic. Based on the hybrid and efficient model, we employ a Monte Carlo approach and use a quantile regression envelope model for capacity decoupling analysis. Using the Shanghai multi-airport region as a case study, the model’s performance is validated from the perspectives of operation time and traffic throughput. The results show that our model accurately represents traffic dynamics and estimates delays within an acceptable margin of error. The capacity decoupling analysis effectively captures the interdependence in traffic flow caused by resource sharing, both within a single airport and between airports.

An airport slot is the core resource in the air transportation system. In most busy airports in China, airline demand significantly exceeds the available slot capacity. Scientific and reasonable slot allocation techniques and methods can improve the operational efficiency and benefits of multi-airport systems. Existing research has predominantly addressed slot allocation optimization for individual airports; however, there are differences in the functional positioning and resource allocation during multi-airport slot optimization, which makes cooperative optimization in the context of multi-airport slot allocation difficult. The dynamic sharing of airspace capacity in multi-airport systems is crucial for optimizing airport slot allocation and improving resource utilization efficiency. This study develops a multi-objective optimization model incorporating coupled airspace capacity relationships within multi-airport systems and the fairness of airlines and airports in order to realize the optimal utilization of multi-airport system resources, considering specialized 24 h airport slot coordination parameter patterns and slot firebreaks in China. Finally, the validity and scalability of the model are verified using real flight data from three airports in the Beijing airport terminal area, and simulations are conducted to verify the model. The findings provide a solid reference for the optimization of airport slot timetables in multi-airport systems, having both important theoretical value and practical significance.

In view of the common U-shaped apron structure of large- and medium-sized airports at home and abroad, this study considered the optimization design and performance evaluation of the U-shaped apron operation procedure. First, by analyzing the physical structure characteristics and traffic operation characteristics of the U-shaped area, exclusive, partition-shared, and global-shared operation procedures of the U-shaped area were designed, and differentiated apron-operation rules and traffic models were constructed for different types of operation procedures. Then, from the perspectives of safety, efficiency, and environmental protection, a multi-dimensional evaluation index system of U-shaped area operation performance is established, and a classification measurement and comprehensive evaluation method based on critique is proposed. Finally, a traffic simulation model was established based on airport network topology modeling. We used Monte Carlo methods for the simulation in Python 3.6, and the experimental results show that, in the scenario of high-density traffic operation, compared with exclusive and partition-shared procedures, the implementation effect of the global shared procedure is very significant, and the apron operation capacity increased by 14.8% and 5.0%, respectively. The probability of aircraft conflict decreased by 32.2% and 11.8%, respectively, and the time of single conflict relief decreased by 16.1 s and 10.6 s, respectively. The average resource utilization in each U-shaped area increased by 66% and 25%, respectively, while the average daily carbon emissions of a single aircraft were reduced by 16.7 kg and 11.0 kg and the average daily fuel consumption of a single aircraft were reduced by 3.6 kg and 2.4 kg, respectively. The proposed method is scientific and effective and can provide theoretical and methodological support for optimizing the configuration of the scene operation mode of complex airports and for improving flight operation efficiency.

Over time, the rapid expansion of civil aviation infrastructure has led to the establishment of multi-airport systems (MASs) or Metroplex, where airports situated in close proximity form interconnected networks. Given that individual airport capacities often fall short of meeting flight scheduling demands, devising effective multi-airport flight scheduling methods becomes imperative. This article introduces a novel MAS slot expansion configuration framework centered on coupling terminal areas. In contrast to conventional airport capacity slot expansion approaches, this framework demonstrates superior configurational efficacy within respective airport terminal environments. The model outlined in this research identifies the terminal control sector as the pivotal resource node within the interconnected terminal area, aiming to maximize the total expanded slots while minimizing the overall unfairness among airports within the terminal airspace. Employing the ε-constraint method facilitates the transformation of the minimization objective into solvable constraint conditions. Subsequently, leveraging Beijing Metroplex as a case study, the research devises benchmark, single-airport, multi-airport minimum, and multi-airport maximum scenarios to compare and analyze configuration outcomes in terms of key resource allocation impacts and coupled resource utilization efficiencies. Ultimately, employing the AirTOp fast-time simulation model validates each scenario, demonstrating that the proposed configuration method yields reduced delay levels and fewer conflicts in simulation environments.

Air carriers shall not readily relinquish their held flight slots. In cases where the historical flight slot pool cannot be easily altered, a pressing need arises for an allocation method that can efficiently utilize the incremental resources of these time slots. This paper presents an integer planning model to address the efficient allocation of incremental airport time slot resources. The model considers the capacity of key resource nodes and flight waveforms as constraints to maximize the total incremental slots. Moreover, it considers the adaptation of strategic and tactical optimization. After conducting a case study using Beijing Capital International Airport for verification, the proposed model effectively reduces potential operational delays by 66.27% while adding 366 to 397-time slots. Notably, the model demonstrates remarkable delay reduction capabilities and can serve as a valuable decision-support tool for the incremental allocation of time slots.

The update and iteration of the airport facilities completed in the runway operation system raise a request for more scientific control operation restrictions. In the old, optimized method of flight slot, no consideration was given to the runway operation strategy. As a result, the flight slot failed to meet the operation restriction and would incur unavoidable delays. This paper sets the research objective as the system composed of an apron, runway entrance and exit, and parallel runway. It focuses on matching the corresponding relationship between time and space of flights in the studied system. It establishes three flight slot optimization models to meet the requirements of isolated operation, semi-mixed operation, and mixed operation, respectively. On a practical level, the computer simulation software AirTOp is employed for simulation verification in the example of Wuhan Tianhe Airport. The results show that the delay in the isolation operation mode is reduced by about 59%, the semi-mixed operating mode reduces delays by about 48%, and mixed operating mode delays are reduced by approximately 52%. Therefore, it proves its feasibility of effective reduction in overall delay and its ability to provide decision support for the allocation of the flight time resource in parallel dual runway airports.