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Machine learning-based conflict-free trajectory generation

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  • Yun-Xiang Han

Abstract

With the rapid development of the aviation industry, air traffic flow is showing a rapid growth trend, and the mutual influence and interference between aircraft in the airspace are also increasing. In order to ensure the safe and orderly operation of air traffic flow, it is urgent to propose efficient conflict-free trajectory generation methods. The development of artificial intelligence technology provides a new way for the design of conflict-free trajectory generation algorithms. As a consequence, machine learning can be applied to conflict-free trajectory generation. Intelligent agents learn autonomously in their interactions with the environment, thus possessing the ability to make autonomous decisions. Simulation experiments in different scenarios have shown that the algorithm proposed is effective.

Suggested Citation

  • Yun-Xiang Han, 2025. "Machine learning-based conflict-free trajectory generation," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 49(2), pages 174-185.
    • Handle: RePEc:ids:ijisen:v:49:y:2025:i:2:p:174-185
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