Aiming at the scenario of the integrated operation of Unmanned Aerial Vehicles (UAVs) and transport aviation in the airport controlled airspace under the concept of urban air mobility, this paper proposes an airspace operation safety risk assessment method. Firstly, considering the maneuverability of UAVs and the position error of aircraft, a double-layer collision protection volume model is proposed; then, the Monte Carlo simulation method is used to simulate the aircraft error and calculate the collision probability. Furthermore, an improved Reich model suitable for the collision risk assessment of UAV routes and take-off and landing routes is proposed. Based on the improved Reich model, a risk assessment of UAV routes around a domestic hub airport is carried out. The results show that the collision risk between the Runway 33 landing route of the airport and the UAV operation route does not meet the Target Level of Safety (TLS) requirements. The study found that reducing the altitude and flight speed of the UAV route can reduce the collision risk, while changing the UAV route flow will not affect the collision risk.

Air traffic flow management has been a major means for balancing air traffic demand and airport or airspace capacity to reduce congestion and flight delays. However, unpredictable factors, such as weather and equipment malfunctions, can cause dynamic changes in airport and sector capacity, resulting in significant alterations to optimized flight schedules and the calculated pre-departure slots. Therefore, taking into account capacity uncertainties is essential to create a more resilient flight schedule. This paper addresses the flight pre-departure sequencing issue and introduces a capacity uncertainty model for optimizing flight schedule at the airport network level. The goal of the model is to reduce the total cost of flight delays while increasing the robustness of the optimized schedule. A chance-constrained model is developed to address the capacity uncertainty of airports and sectors, and the significance of airports and sectors in the airport network is considered when setting the violation probability. The performance of the model is evaluated using real flight data by comparing them with the results of the deterministic model. The development of the model based on the characteristics of this special optimization mechanism can significantly enhance its performance in addressing the pre-departure flight scheduling problem at the airport network level.

Urban air mobility (UAM) extends urban transportation to low-altitude airspace using electric vertical take-off and landing (eVTOL) vehicle to reduce traffic congestion. The vertical take-off and landing (VTOL) site connecting ground and air transport is the critical infrastructure of the UAM. Determining its locations is essential for the design and operation of the air route. This study focuses on the problem of the location of the VTOL site, using Shenzhen as the study area, and establishes an integer programming model with the objective of maximizing travel cost savings to identify the optimal locations of the VTOL sites. This study is different from existing ones in that it explicitly considers the three-dimensional spatial availability of VTOL sites. Geographic information system (GIS) tools are used to identify locations that satisfy two-dimensional (2D) planar availability, and an obstacle assessment model of the approach/departure and transitional surfaces of the VTOL site is built to further screen the locations. The selected potential sites are used as input to the integer programming model, ensuring that the locations identified to establish the VTOL site are optimal. The impact of the number of VTOL sites, the user's transfer time at the VTOL sites, and the eVTOL pricing on the model solution is also discussed. Although this study uses Shenzhen as a research object, the proposed methodology is generalized and applicable to any other city or region, providing recommendations and references for initial planning and related operations of the UAM in selected areas.

Most Level 3 airports around the world suffer severe congestion and flight delays. Airlines have to obtain airport slots in order to schedule flights at such airports. The main way for airlines to acquire slots is primary slot allocation, in which a slot coordinator distributes slots to airlines according to certain rules and regulations. Due to excessive demand for slots and restrictions on allocation rules, it is difficult for some airlines to obtain the desired slots in this manner. Another way for airlines to obtain slots is through secondary slot trading, in which slots can be redistributed among airlines without being returned to slot pool. The secondary trading of airport slots has played a positive role in promoting the efficient utilization of slot resources, but systematic studies are insufficient. This paper discusses the reasons for the existence of slot secondary trading, sorts out the main policies and rules governing the mechanism, investigates its impacts on the industry and society, and points out the major problems and challenges. The paper provides a reference for subsequent research and practical application of airport slot secondary trading in the future.