Enhanced self-separation decision making for autonomous flight operations in air corridors

Zhaoxuan Liu, Maolin Wang and Zhiyong Liu

Journal of Air Transport Management, 2025, vol. 124, issue C

Abstract: This paper discusses the emergency self-separation decision-making for autonomous aircraft operating in a high-density air corridor. Air corridors are longish airspace volumes, where multiple self-separated aircraft fly sequentially without instructions from the Air Traffic Controllers (ATCOs). However, due to high traffic volume and limited inter-distance between aircraft, the trailing aircraft becomes more conflict sensitive to environment changes (for instance, a sudden deceleration in the preceding aircraft). Therefore, to realize high traffic throughput while maintaining operation safety, an enhanced multi-attribute decision making (MADM) framework is presented in this paper to address the need for appropriate maneuver determination in a close proximity situation. Specifically, we decompose the MADM scheme into two main steps. In the first step, four candidate maneuver options are generated under different self-separation methodologies. Each candidate option is then evaluated via multiple attributes, which represent various performance objectives of the aircraft. In the second step, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is used to determine the optimal maneuver that realizes an adequate tradeoff among the competing objectives. By simulating aircraft maneuvers in diverse emergency scenarios and with various corridor traffic settings, experimental results have successfully demonstrated the effectiveness of the proposed MADM-based self-separation mechanism.

Keywords: Air traffic management (ATM); Air corridor; Autonomous flight operation; Multi-attribute decision making (MADM); Self-separation (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jaitra:v:124:y:2025:i:c:s0969699724001868

DOI: 10.1016/j.jairtraman.2024.102721

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