期刊文献+

基于蒙特卡罗仿真的汇聚冲突风险评估

An Assessment of the Conflict Risk of Converging Air Traffic using Monte Carlo Simulation
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摘要 为了揭示汇聚交通场景中冲突风险的总体水平以及动态变化规律,提出了基于蒙特卡罗仿真的汇聚交通流冲突风险评估方法。通过分析汇聚航路的几何特性,构建了汇聚交通流的冲突航段模型,从而确定汇聚交通流产生冲突的范围。并设计了基于蒙特卡罗仿真的冲突风险评估方法,通过实时对比四维轨迹,对冲突率、冲突严重程度、冲突风险、总冲突风险等指标进行了评估,实现了对汇聚交通流从局部到整体,从宏观到微观的冲突风险分析。最后,针对A593航路与R343航路在VMB点汇聚的实际汇聚交通场景,在分析实际运行数据分布的基础上对其冲突风险进行了评估。 In order to unveil the overall states and dynamic variation of conflict risks for converging air traffic,a conflict risk assessment method based on Monte Carlo simulation was proposed.Based on the analysis of the geometry characteristic of the converging airways,the conflict route segment model is proposed to determine the conflict ranges that are caused by converging air traffic.The conflict risk assessment method based on the Monte Carlo Simulation was designed.The conflict risks of converging air traffic were assessed from macroscopic and microscopic levels by comparing the 4Dtrajectories,conflict rate,conflict severity,conflict risk and total conflict risks.Finally,the conflict risks were assessed for the convergence of Route A593 and Route R343 at VMB by the simulation as an example based on statistical analysis of historical operation data.
出处 《交通信息与安全》 2015年第4期93-99,共7页 Journal of Transport Information and Safety
基金 国家自然科学基金项目(批准号:71401072) 江苏省自然科学基金项目(批准号:BK20130814) 中央高校基本科研业务费专项资金(批准号:NS2013069)资助
关键词 航空运输 风险评估 冲突 汇聚交通流 蒙特卡罗仿真 air transportation risk assessment conflict converging air traffic Monte Carlo simulation
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  • 1RUIZ S, PIERA M, POZO I. A medium term conflict detection and resolution system for terminal maneuvering area based on spatial data and 4D trajectories[J]. Transportation Research: Part C, 2013, 26 : 396-417.
  • 2HANCERLIOGULLARI G, RABADI G, AL-SALEM A H, et al. Greedy algorithms and metaheuristics for a multiple runway combined arrival-departure aircraft sequencing problem[J]. Journal of Air Transport Management, 2013, 32: 39-48.
  • 3ZuNIGA C A, PIERA M A, RUIZ S. A CD&CR causal model based on path shortening/path stretching techniques[ J ]. Transportation Research : Part C, 2013, 33: 238-256.
  • 4SCHROEDER J A. A perspective on NASA Ames air traffic management research[ C ] // 9th AIAA Aviation Technology, Integration, and Operations Conference (ATIO). [S.l. ] : AIAA, 2009: 7054-1-7054-16.
  • 5BAR-SHALOM Y, LI X R. Estimation with applications to tracking and navigation: theory algorithms and software[ M]. [ S. l. ] : John Wiley Sons, Inc., 2001 : 466-476.
  • 6HWANG I. Air traffic surveillance and control using hybrid estimation and protocol-based conflict resolution [ D ]. Stanford : Stanford University, 2003.
  • 7SEAH C E, HWANG I. State estimation for stochastic linear hybrid systems with continuous-state-dependent transitions: an IMM approach[J]. IEEE Transactions on Aerospace and Electronics Systems, 2009, 45 ( 1 ) : 376-392.
  • 8SEAH C E, HWANG I. Algorithm for performance analysis of the IMM algorithm[J]. IEEE Transactions on Aerospace and Electronic Systems, 2011, 47 ( 2 ) : 1114-1124.
  • 9FUKUDA Y, SHIRAKAWA M, SENOGUCHI A. Development of trajectory prediction model [ C ]//ENRI International Workshop on ATM/CNS (EIWAC). Tokyo: [s. n. ], 2010: 95-100.
  • 10FAA, Eurocontrol. Common trajectory prediction structure and terminology in support of SESAR & NextGen[R]. Bretigny: EEC, 2010.

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