期刊文献+

基于多智能体的机场空侧运行仿真研究 被引量:1

Research on Airport Airside Operation Simulation Based on Multi-Agent
下载PDF
导出
摘要 针对传统机场运行仿真过程中灵活性、智能性的不足,将多智能体(Multi-Agent)理论和方法应用到机场空侧运行仿真中,提出了基于多智能体的机场运行仿真方法。介绍了机场空侧运行仿真系统体系结构,详细设计了与之相关的Agent,包括航空器、管制员和空管自动化系统对应的Agent等,分析探讨了各Agent的内部运行机制、功能与行为模块以及网络通信过程,构建了系统的整体框架并基于JADE平台实现了系统搭建,验证了模型和方法的准确性。 Considering the lack of flexibility and intelligence in the process of traditional airport operation simulation, a simulation method based on multi- agent is put forward. Firstly, the system architecture of airside operation simulation is introduced. And the related agents are designed, such as aircraft, controllers agent, etc. Then the analysis of internal operation mechanism of each agent, and their function and behavior modules, coupled with the network communication process between them, are set forth. Finally, the overall system framework is constructed and realized through the JADE platform. Case study proves the accuracy of the model and the method.
出处 《航空计算技术》 2015年第4期51-56,共6页 Aeronautical Computing Technique
基金 国家自然科学基金项目资助(U1433125) 江苏省自然科学基金项目资助(BK20141413) 民航科技引导资金项目资助(14014J0340035) 中央高校基本科研业务费专项资金资助(NS2014065) 美国波音公司资助项目(2014-SDB-11)
关键词 多智能体 机场空侧运行 模型建设 仿真系统 人工智能 multi- agent airport airside operation modeling simulation system artificial intelligence
  • 相关文献

参考文献5

  • 1Wolfe S R. Supporting Air Traffic Flow Management with A- gents [ C ]//AIAA Spring Symposium: Interaction Challenges for Intelligent Assistants,2007 : 137 - 138.
  • 2Hexmoor H, Heng T. Air Traffic Control Agents:Landing and Collision Avoidance[ C ]//International Conference in Artifi- cial Intelligence, HR Arabnia,2000.
  • 3Pechoucek M, Sislak D, Pavlicek D, et al. Autonomous A- gents for Air- traffic Deconfliction [ C ]//Proceedings of the Fifth International Joint Conference on Autonomous Agents and Muhiagent Systems, ACM ,2006 : 1498 - 1505.
  • 4Hoc J M, Carlier X. Role of a Common Frame of Reference in Cognitive Cooperation:Sharing Tasks Between Agents in Air Traffic Control [ J ]. Cognition, Technology & Work, 2002,4 (1) :37 -47.
  • 5尤杰,韩松臣.基于多Agent的机场场面最优滑行路径算法[J].交通运输工程学报,2009,9(1):109-112. 被引量:14

二级参考文献7

  • 1李实永.MAS在智能交通系统中的应用研究[J].城市交通,2006,4(5):78-80. 被引量:3
  • 2李薇,张凤鸣.多Agent技术研究与应用[J].微计算机信息,2006(08X):293-295. 被引量:37
  • 3ZHAN F B. Three fastest shortest path algorithms on real road networks[J]. Journal of Geographic Information and Decision Analysis, 1997, 1(1): 69-82.
  • 4JI Rong, HAN Song chen. Route optimizing algorithm of airport surface based on GIS[J].Transaction of Nanjing University of Aeronautics & Astronautics, 2005, 22(1) : 71-77.
  • 5IDRIS H, CLARKE J P, BHUVA R, et al. Queuing model for taxi out time estimation[R]. Cambridge: Massachusetts Institute of Technology, 2001.
  • 6SMITH R G. The contract net protocol: high-level communication and control in a distributed problem solver[J].IEEE Transactions on Computers, 1980, 29(12): 1104-1113.
  • 7计会凤,徐爱功,隋达嵬.Dijkstra算法的设计与实现[J].辽宁工程技术大学学报(自然科学版),2008,27(A01):222-223. 被引量:7

共引文献13

同被引文献42

引证文献1

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部