Develops a risk assessment method for airspace safety in autonomous aircraft, suggesting effective real-time management strategies.
To meet the requirement of refined airspace risk assessment under the autonomous operation mode, this paper proposes an airspace risk calculation method based on potential field theory. First, an aircraft ellipsoidal risk zone is established to define the risk influence range. Based on the airspace grid and potential field function, a risk assessment model is constructed that considers the real-time impacts of distance, speed, heading, and other factors to model the radiation effect of aircraft operation risk. Second, two simulation scenarios are set up to validate the model’s effectiveness and analyze differences in the spatio-temporal distribution of airspace risk. Additionally, multiple conflict scenarios are established. The correlation coefficients between conflict indicators and average airspace risk values for different flights are calculated to demonstrate the model’s reasonableness. Finally, an airspace hotspot grid marking method is developed. Hotspot distributions are visualized across various grid scales, realizing multi-granularity awareness of the airspace safety situation from a spatial geographic perspective. Simulation results show the model effectively characterizes the real-time spatio-temporal distribution of airspace risk. As the number of simulated aircraft increases, the correlation between conflict indicators and average risk values becomes increasingly strong and stable, verifying the model’s validity. Furthermore, multi-granularity grids reveal hotspot distribution details at different spatial resolutions, providing a reference for on-board auxiliary decision-making systems to make trajectory adjustments.
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Zhang et al. (2026) studied this question.
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