With the continuous opening of low-altitude airspace and the development of aircraft such as electric vertical takeoff and landing (eVTOL) vehicles, urban air traffic has become a sustainable and green development direction for future transportation. Air route networks, as a mainstream design scheme for air traffic, are able to provide prerequisites for eVTOL and other green aircraft to enter urban airspace for safe operation, among which air route planning is a fundamental component of air route network design. Currently, most of the research on aircraft path planning is performed in free airspace, lacking the analysis and processing for the complex operation environment, which has led to the high risk and large operation cost of path planning results, failing to meet the demand for safe and efficient development in the future. Aiming at the above problems, eVTOL-oriented air route planning research was carried out. Firstly, the urban low-altitude airspace structure was planned, and the operational levels of eVTOL were clarified; this was followed by introducing the urban dynamic air–ground risk factors and constructing a dynamic risk assessment model containing risk level information; finally, the improved A* algorithm based on the risk cost was employed to plan the eVTOL air route network, which finally realized the purpose of short path length and low total risk. The simulation results showed that the route generated by the improved A* algorithm could reduce the risk cost by at least 30% with a relatively small path cost, which ensured the operation efficiency and safety of eVTOLs and laid the foundation for the further sustainable and green development of urban airspace in the future.

The telemetry data structure is the embodiment of satellite telemetry format, the rationality and correctness of which determine the satellite telemetry capacity as well as transmission capability. Conventional satellite telemetry data structure designs excessively depend on manual experience, easily leading to problems such as waste of satellite resources, low telemetry transmission efficiency and unintuitive ground decoding. In this paper, a novel method was proposed to optimize the design of satellite telemetry data structure, based on rasterized modeling to visualize the design constraints, and an improved ant colony algorithm with grey relational analysis to optimize the telemetry data structure. The method is not only effective in preventing the deficiencies of conventional approaches, but also beneficial to the rational allocation of telemetry resources. The feasibility was verified by the telemetry data of a satellite with DFH-4 platform, and the results showed favorable convergence, along with valid improvement of the design process efficiency and application effect.