Aircraft Flight Autonomous Decision-Making Method Based on Target Predicted Trajectory and Markov Decision Process
In this paper, in order to enhance the autonomous operation capabilities of aircraft and ensure their operational safety and efficiency, we propose an autonomous decision-making framework based on target motion state prediction combined with the Markov Decision Process, namely IMM-MDP architecture....
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MDPI AG
2024-12-01
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| Series: | Actuators |
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| Online Access: | https://www.mdpi.com/2076-0825/13/12/496 |
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| author | Yang Zhou Xinmin Tang Xuanming Ren |
| author_facet | Yang Zhou Xinmin Tang Xuanming Ren |
| author_sort | Yang Zhou |
| collection | DOAJ |
| description | In this paper, in order to enhance the autonomous operation capabilities of aircraft and ensure their operational safety and efficiency, we propose an autonomous decision-making framework based on target motion state prediction combined with the Markov Decision Process, namely IMM-MDP architecture. Firstly, our own aircraft utilizes the IMM algorithm to achieve the state prediction of the target; building upon the existing algorithmic structure, the proposed framework improves model sets within the IMM algorithm by incorporating climb and turn models and refines the motion modes of aircraft during the cruise phase, gathering corresponding sub-models to predict different motion modes and enhance the prediction accuracy of the target. Secondly, we adopt the Markov Decision Process as the autonomous decision-making method for the own aircraft, proposing a method by which to calculate the optimal decision sequence based on the prediction scenarios of the IMM algorithm; that is, in both multi-step prediction and single-step prediction scenarios, the payoff values of different action strategies at each decision moment are calculated to obtain the optimal decision sequence. The experimental results show that the IMM algorithm with the improved model set, described in this paper, is more accurate than the IMM algorithm and prediction results of the current statistical model, as described in the literature. We also set up a multi-aircraft operation scenario, comparing the IMM-MDP decision framework proposed in this paper with the Monte Carlo and MPC decision models, thus demonstrating that the proposed framework provides better decisions while ensuring safety. Due to the target state prediction and updating, this method also demonstrates better real-time performance and practicality. |
| format | Article |
| id | doaj-art-c4e0b3ba8768461489014adc91de77df |
| institution | OA Journals |
| issn | 2076-0825 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Actuators |
| spelling | doaj-art-c4e0b3ba8768461489014adc91de77df2025-08-20T02:00:55ZengMDPI AGActuators2076-08252024-12-01131249610.3390/act13120496Aircraft Flight Autonomous Decision-Making Method Based on Target Predicted Trajectory and Markov Decision ProcessYang Zhou0Xinmin Tang1Xuanming Ren2College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaSchool of Transportation Science and Engineering, Civil Aviation University of China, Tianjin 300300, ChinaCollege of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaIn this paper, in order to enhance the autonomous operation capabilities of aircraft and ensure their operational safety and efficiency, we propose an autonomous decision-making framework based on target motion state prediction combined with the Markov Decision Process, namely IMM-MDP architecture. Firstly, our own aircraft utilizes the IMM algorithm to achieve the state prediction of the target; building upon the existing algorithmic structure, the proposed framework improves model sets within the IMM algorithm by incorporating climb and turn models and refines the motion modes of aircraft during the cruise phase, gathering corresponding sub-models to predict different motion modes and enhance the prediction accuracy of the target. Secondly, we adopt the Markov Decision Process as the autonomous decision-making method for the own aircraft, proposing a method by which to calculate the optimal decision sequence based on the prediction scenarios of the IMM algorithm; that is, in both multi-step prediction and single-step prediction scenarios, the payoff values of different action strategies at each decision moment are calculated to obtain the optimal decision sequence. The experimental results show that the IMM algorithm with the improved model set, described in this paper, is more accurate than the IMM algorithm and prediction results of the current statistical model, as described in the literature. We also set up a multi-aircraft operation scenario, comparing the IMM-MDP decision framework proposed in this paper with the Monte Carlo and MPC decision models, thus demonstrating that the proposed framework provides better decisions while ensuring safety. Due to the target state prediction and updating, this method also demonstrates better real-time performance and practicality.https://www.mdpi.com/2076-0825/13/12/496autonomous decision-makingtarget motion state predictioninteractive multiple model (IMM)Markov Decision Process (MDP) |
| spellingShingle | Yang Zhou Xinmin Tang Xuanming Ren Aircraft Flight Autonomous Decision-Making Method Based on Target Predicted Trajectory and Markov Decision Process Actuators autonomous decision-making target motion state prediction interactive multiple model (IMM) Markov Decision Process (MDP) |
| title | Aircraft Flight Autonomous Decision-Making Method Based on Target Predicted Trajectory and Markov Decision Process |
| title_full | Aircraft Flight Autonomous Decision-Making Method Based on Target Predicted Trajectory and Markov Decision Process |
| title_fullStr | Aircraft Flight Autonomous Decision-Making Method Based on Target Predicted Trajectory and Markov Decision Process |
| title_full_unstemmed | Aircraft Flight Autonomous Decision-Making Method Based on Target Predicted Trajectory and Markov Decision Process |
| title_short | Aircraft Flight Autonomous Decision-Making Method Based on Target Predicted Trajectory and Markov Decision Process |
| title_sort | aircraft flight autonomous decision making method based on target predicted trajectory and markov decision process |
| topic | autonomous decision-making target motion state prediction interactive multiple model (IMM) Markov Decision Process (MDP) |
| url | https://www.mdpi.com/2076-0825/13/12/496 |
| work_keys_str_mv | AT yangzhou aircraftflightautonomousdecisionmakingmethodbasedontargetpredictedtrajectoryandmarkovdecisionprocess AT xinmintang aircraftflightautonomousdecisionmakingmethodbasedontargetpredictedtrajectoryandmarkovdecisionprocess AT xuanmingren aircraftflightautonomousdecisionmakingmethodbasedontargetpredictedtrajectoryandmarkovdecisionprocess |