In an effort to maintain safety while satisfying growing air traffic demand,air navigation service providers are considering the inclusion of advisory systems to identify potential conflicts and propose resolution com...In an effort to maintain safety while satisfying growing air traffic demand,air navigation service providers are considering the inclusion of advisory systems to identify potential conflicts and propose resolution commands for the air traffic controller to verify and issue to aircraft.To understand the potential workload implications of introducing advisory conflict-detection and resolution tools,this paper examines a metric of controller taskload:how many resolution commands an air traffic controller issues under the guidance of an advisory system.Through a simulation study,the research presented here evaluates how the underlying protocol of a conflict-resolution tool affects the controller taskload(system demands)associated with the conflict-resolution process,and implicitly the controller workload(physical and psychological demands).Ultimately,evidence indicates that there is significant flexibility in the design of conflict-resolution algorithms supporting an advisory system.展开更多
Conflict Detection and Resolution（CD＆R） is the key to ensure aviation safety based on Trajectory Prediction（TP）. Uncertainties that affect aircraft motions cause difficulty in an accurate prediction of the trajec...Conflict Detection and Resolution（CD＆R） is the key to ensure aviation safety based on Trajectory Prediction（TP）. Uncertainties that affect aircraft motions cause difficulty in an accurate prediction of the trajectory, especially in the context of four-dimensional（4D） Trajectory-Based Operation（4DTBO）, which brings the uncertainty of pilot intent. This study draws on the idea of time geography, and turns the research focus of CD＆R from TP to an analysis of the aircraft reachable space constrained by 4D waypoint constraints. The concepts of space–time reachability of aircraft and space–time potential conflict space are proposed. A novel pre-CD＆R scheme for multiple aircraft is established. A key advantage of the scheme is that the uncertainty of pilot intent is accounted for via a Space-Time Prism（STP） for aircraft. Conflict detection is performed by verifying whether the STPs of aircraft intersect or not, and conflict resolution is performed by planning a conflict-free space–time trajectory avoiding intersection. Numerical examples are presented to validate the efficiency of the proposed scheme.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
通过对国内某航路管制单位的冲突探测与解脱数据收集和数据分析,形成贴合实际运行的航路管制规则库,采用基于BADA(Base of Aircraft data,一种由欧洲空管开发维护并应用比较成熟的飞行性能模型)的轨迹生成算法,通过实地调研和数据收集,...通过对国内某航路管制单位的冲突探测与解脱数据收集和数据分析,形成贴合实际运行的航路管制规则库,采用基于BADA(Base of Aircraft data,一种由欧洲空管开发维护并应用比较成熟的飞行性能模型)的轨迹生成算法,通过实地调研和数据收集,结合实际管制运行中的航路冲突标准,建立双机基于管制规则库和决策树的航路冲突探测与解脱模型.选取国内A593航路,使用JAVA语言完成了仿真系统开发,并导入飞行计划数据实现了实例验证.最终的仿真结果表明模型成功解脱常见航路冲突,保证了与实际航路管制运行的一致性.展开更多
基金funded by NASA(No.NNX08AY52A)FAA Award(No.07-C-NEGIT)+1 种基金Amendment(Nos.005,010,020)Air Force Contract(No.FA9550-08-1-0375)。
文摘In an effort to maintain safety while satisfying growing air traffic demand,air navigation service providers are considering the inclusion of advisory systems to identify potential conflicts and propose resolution commands for the air traffic controller to verify and issue to aircraft.To understand the potential workload implications of introducing advisory conflict-detection and resolution tools,this paper examines a metric of controller taskload:how many resolution commands an air traffic controller issues under the guidance of an advisory system.Through a simulation study,the research presented here evaluates how the underlying protocol of a conflict-resolution tool affects the controller taskload(system demands)associated with the conflict-resolution process,and implicitly the controller workload(physical and psychological demands).Ultimately,evidence indicates that there is significant flexibility in the design of conflict-resolution algorithms supporting an advisory system.
基金financial support from the Civil Aviation Joint Funds of the National Natural Science Foundation of China (No’s.U1533203,61179069)
文摘Conflict Detection and Resolution（CD＆R） is the key to ensure aviation safety based on Trajectory Prediction（TP）. Uncertainties that affect aircraft motions cause difficulty in an accurate prediction of the trajectory, especially in the context of four-dimensional（4D） Trajectory-Based Operation（4DTBO）, which brings the uncertainty of pilot intent. This study draws on the idea of time geography, and turns the research focus of CD＆R from TP to an analysis of the aircraft reachable space constrained by 4D waypoint constraints. The concepts of space–time reachability of aircraft and space–time potential conflict space are proposed. A novel pre-CD＆R scheme for multiple aircraft is established. A key advantage of the scheme is that the uncertainty of pilot intent is accounted for via a Space-Time Prism（STP） for aircraft. Conflict detection is performed by verifying whether the STPs of aircraft intersect or not, and conflict resolution is performed by planning a conflict-free space–time trajectory avoiding intersection. Numerical examples are presented to validate the efficiency of the proposed scheme.
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.
文摘通过对国内某航路管制单位的冲突探测与解脱数据收集和数据分析,形成贴合实际运行的航路管制规则库,采用基于BADA(Base of Aircraft data,一种由欧洲空管开发维护并应用比较成熟的飞行性能模型)的轨迹生成算法,通过实地调研和数据收集,结合实际管制运行中的航路冲突标准,建立双机基于管制规则库和决策树的航路冲突探测与解脱模型.选取国内A593航路,使用JAVA语言完成了仿真系统开发,并导入飞行计划数据实现了实例验证.最终的仿真结果表明模型成功解脱常见航路冲突,保证了与实际航路管制运行的一致性.
