In order to grasp the evolution of flight conflict amount accurately and to forecast the amount, chaos in flight conflicts is studied. Firstly, a fault tree of flight conflicts is established based on the man-machine-...In order to grasp the evolution of flight conflict amount accurately and to forecast the amount, chaos in flight conflicts is studied. Firstly, a fault tree of flight conflicts is established based on the man-machine-environ- ment system engineering theory. The chaotic characteristics of flight conflict are analyzed from the qualitative point of view. Secondly, an improved chaotic algorithm for the largest Lyapunov exponent is proposed based on the small-data method and the wavelet de-noising theory. Chaos in flight conflict time series is identified by the improved chaotic algorithm from the quantitative point of view. Finally, a case study by the chaos forecasting al- gorithm is performed and the results are evaluated by the gray error checking ： Correlative value of posterior error is 0. 220 9〈0. 35, and micro-error probability is 0. 985 3〉0.95. Such results show the chaos forecasting algo- rithm is effective, thus it is feasible to analyze and forecast flight conflict by chaotic theory.展开更多
With the rapid growth of flight flow,the workload of controllers is increasing daily,and handling flight conflicts is the main workload.Therefore,it is necessary to provide more efficient conflict resolution decision-...With the rapid growth of flight flow,the workload of controllers is increasing daily,and handling flight conflicts is the main workload.Therefore,it is necessary to provide more efficient conflict resolution decision-making support for controllers.Due to the limitations of existing methods,they have not been widely used.In this paper,a Deep Reinforcement Learning(DRL)algorithm is proposed to resolve multi-aircraft flight conflict with high solving efficiency.First,the characteristics of multi-aircraft flight conflict problem are analyzed and the problem is modeled based on Markov decision process.Thus,the Independent Deep Q Network(IDQN)algorithm is used to solve the model.Simultaneously,a’downward-compatible’framework that supports dynamic expansion of the number of conflicting aircraft is designed.The model ultimately shows convergence through adequate training.Finally,the test conflict scenarios and indicators were used to verify the validity.In 700 scenarios,85.71%of conflicts were successfully resolved,and 71.51%of aircraft can reach destinations within 150 s around original arrival times.By contrast,conflict resolution algorithm based on DRL has great advantages in solution speed.The method proposed offers the possibility of decision-making support for controllers and reduce workload of controllers in future high-density airspace environment.展开更多
In order to improve the accuracy of free flight conflict detection and reduce the false alarm rate, an improved flight conflict detection algorithm is proposed based on Gauss-Hermite particle filter（GHPF）. The algor...In order to improve the accuracy of free flight conflict detection and reduce the false alarm rate, an improved flight conflict detection algorithm is proposed based on Gauss-Hermite particle filter（GHPF）. The algorithm improves the traditional flight conflict detection method in two aspects：（i） New observation data are integrated into system state transition probability, and Gauss-Hermite Filter（GHF） is used for generating the importance density function.（ii） GHPF is used for flight trajectory prediction and flight conflict probability calculation. The experimental results show that the accuracy of conflict detection and tracing with GHPF is better than that with standard particle filter. The detected conflict probability is more precise with GHPF, and GHPF is suitable for early free flight conflict detection.展开更多
Describing spatial safety status is crucial for high-density air traffic involving multiple unmanned aerial vehicles （UAVs） in a complex environment. A probabilistic approach is proposed to measure safety situation ...Describing spatial safety status is crucial for high-density air traffic involving multiple unmanned aerial vehicles （UAVs） in a complex environment. A probabilistic approach is proposed to measure safety situation in congested airspace. The occupancy distribution of the airspace is represented with conflict probability between spatial positions and UAV. The concept of a safety envelope related to flight performance and response time is presented first instead of the conventional fixed-size protected zones around aircraft. Consequently, the conflict probability is performance-dependent, and effects of various UAVs on safety can be distinguished. The uncertainty of a UAV future position is explicitly accounted for as Brownian motion. An analytic approximate algorithm for the conflict probability is developed to decrease the computational consumption. The relationship between safety and flight performance are discussed for different response times and prediction intervals. To illustrate the applications of the approach, an experiment of three UAVs in formation flight is performed. In addition, an example of trajectory planning is simulated for one UAV flying over airspace where five UAVs exist. The validation of the approach shows its potential in guaranteeing flight safety in highly dynamic environment.展开更多
航路交叉口的管制调配一直是影响空管效率的核心问题,以往研究多是针对少量架次航空器进行分析,本论文在航迹运行(trajectory based operations,TBO)环境下,基于自主改航对航路交叉口处交叉航班流的预先冲突解脱方法进行研究.首先,基于...航路交叉口的管制调配一直是影响空管效率的核心问题,以往研究多是针对少量架次航空器进行分析,本论文在航迹运行(trajectory based operations,TBO)环境下,基于自主改航对航路交叉口处交叉航班流的预先冲突解脱方法进行研究.首先,基于航空器间水平安全间隔,转换计算航空器过交叉口时应保持的最小纵向时间间隔;其次,提出占用时间窗概念,建立基于占用时间窗的冲突检测模型,并考虑航班流通过时间最短制定综合通行原则,判定冲突中需要改航的航空器;最后,针对航班流通行中传统启发式算法时效性不足的问题,利用转弯角限制缩减可行解空间,并建立以改航时间最短为目标的改航点搜索模型,提高求解速度和搜索精度.以我国东北部典型高空扇区为例,验证所提方法在实际交叉航路运行下的有效性.仿真结果表明:所提冲突解脱方法的多米诺效应指数(domino effect parameter,DEP)相较于传统等待解脱方法降低了64.7%,且传统方法的解脱总用时为所提冲突解脱方法的7.6倍,所提解脱方法对空域稳定性的影响更小,解脱效率更高.展开更多
基金Supported by the Joint Funds of National Natural Science Foundation of China(61039001)~~
文摘In order to grasp the evolution of flight conflict amount accurately and to forecast the amount, chaos in flight conflicts is studied. Firstly, a fault tree of flight conflicts is established based on the man-machine-environ- ment system engineering theory. The chaotic characteristics of flight conflict are analyzed from the qualitative point of view. Secondly, an improved chaotic algorithm for the largest Lyapunov exponent is proposed based on the small-data method and the wavelet de-noising theory. Chaos in flight conflict time series is identified by the improved chaotic algorithm from the quantitative point of view. Finally, a case study by the chaos forecasting al- gorithm is performed and the results are evaluated by the gray error checking ： Correlative value of posterior error is 0. 220 9〈0. 35, and micro-error probability is 0. 985 3〉0.95. Such results show the chaos forecasting algo- rithm is effective, thus it is feasible to analyze and forecast flight conflict by chaotic theory.
基金supported by Safety Ability Project of Civil Aviation Administration of China(No.TM 2018-5-1/2)the Open Foundation project of The Graduate Student Innovation Base,China(Laboratory)of Nanjing University of Aeronautics and Astronautics,China(No.kfjj20190720)。
文摘With the rapid growth of flight flow,the workload of controllers is increasing daily,and handling flight conflicts is the main workload.Therefore,it is necessary to provide more efficient conflict resolution decision-making support for controllers.Due to the limitations of existing methods,they have not been widely used.In this paper,a Deep Reinforcement Learning(DRL)algorithm is proposed to resolve multi-aircraft flight conflict with high solving efficiency.First,the characteristics of multi-aircraft flight conflict problem are analyzed and the problem is modeled based on Markov decision process.Thus,the Independent Deep Q Network(IDQN)algorithm is used to solve the model.Simultaneously,a’downward-compatible’framework that supports dynamic expansion of the number of conflicting aircraft is designed.The model ultimately shows convergence through adequate training.Finally,the test conflict scenarios and indicators were used to verify the validity.In 700 scenarios,85.71%of conflicts were successfully resolved,and 71.51%of aircraft can reach destinations within 150 s around original arrival times.By contrast,conflict resolution algorithm based on DRL has great advantages in solution speed.The method proposed offers the possibility of decision-making support for controllers and reduce workload of controllers in future high-density airspace environment.
基金Supported by the Joint Project of National Natural Science Foundation of ChinaCivil Aviation Administration of China(U1333116)
文摘In order to improve the accuracy of free flight conflict detection and reduce the false alarm rate, an improved flight conflict detection algorithm is proposed based on Gauss-Hermite particle filter（GHPF）. The algorithm improves the traditional flight conflict detection method in two aspects：（i） New observation data are integrated into system state transition probability, and Gauss-Hermite Filter（GHF） is used for generating the importance density function.（ii） GHPF is used for flight trajectory prediction and flight conflict probability calculation. The experimental results show that the accuracy of conflict detection and tracing with GHPF is better than that with standard particle filter. The detected conflict probability is more precise with GHPF, and GHPF is suitable for early free flight conflict detection.
基金supported by the National Basic Research Program of China (No.2011CB707002)
文摘Describing spatial safety status is crucial for high-density air traffic involving multiple unmanned aerial vehicles （UAVs） in a complex environment. A probabilistic approach is proposed to measure safety situation in congested airspace. The occupancy distribution of the airspace is represented with conflict probability between spatial positions and UAV. The concept of a safety envelope related to flight performance and response time is presented first instead of the conventional fixed-size protected zones around aircraft. Consequently, the conflict probability is performance-dependent, and effects of various UAVs on safety can be distinguished. The uncertainty of a UAV future position is explicitly accounted for as Brownian motion. An analytic approximate algorithm for the conflict probability is developed to decrease the computational consumption. The relationship between safety and flight performance are discussed for different response times and prediction intervals. To illustrate the applications of the approach, an experiment of three UAVs in formation flight is performed. In addition, an example of trajectory planning is simulated for one UAV flying over airspace where five UAVs exist. The validation of the approach shows its potential in guaranteeing flight safety in highly dynamic environment.
文摘航路交叉口的管制调配一直是影响空管效率的核心问题,以往研究多是针对少量架次航空器进行分析,本论文在航迹运行(trajectory based operations,TBO)环境下,基于自主改航对航路交叉口处交叉航班流的预先冲突解脱方法进行研究.首先,基于航空器间水平安全间隔,转换计算航空器过交叉口时应保持的最小纵向时间间隔;其次,提出占用时间窗概念,建立基于占用时间窗的冲突检测模型,并考虑航班流通过时间最短制定综合通行原则,判定冲突中需要改航的航空器;最后,针对航班流通行中传统启发式算法时效性不足的问题,利用转弯角限制缩减可行解空间,并建立以改航时间最短为目标的改航点搜索模型,提高求解速度和搜索精度.以我国东北部典型高空扇区为例,验证所提方法在实际交叉航路运行下的有效性.仿真结果表明:所提冲突解脱方法的多米诺效应指数(domino effect parameter,DEP)相较于传统等待解脱方法降低了64.7%,且传统方法的解脱总用时为所提冲突解脱方法的7.6倍,所提解脱方法对空域稳定性的影响更小,解脱效率更高.
