基于Petri网的A-SMGCS航空器滑行路由与冲突监控理论研究
|
摘要
建立空地一体化的空中交通管理系统，实现无缝隙空管运行，是新一代民用航空运输系统的战略目标之一。先进场面活动引导和控制系统（Advanced Surface Movement Guidance andControl Systems，A-SMGCS）通过监视场面活动目标（航空器和车辆）并展开管制决策，可支持实现机场范围内的无缝隙运行，将在未来空管系统中扮演重要角色。在A-SMGCS模块化实施方案中，滑行路由模块为活动目标提供无冲突滑行轨迹，冲突监控模块防止活动目标违背场面运行管制规则，因而成为A-SMGCS的关键核心模块。但目前A-SMGCS滑行路由和冲突监控研究多针对特定机场展开，缺乏通用性理论。鉴于此，本文建立了人在环路的A-SMGCS场面运行递阶控制结构，将滑行路由和冲突监控集中到统一的层次化结构中，并引入Petri网建模理论和分析方法对它们分别展开研究，形成了较为系统、完善的A-SMGCS滑行路由与冲突监控理论，为A-SMGCS实施提供具有通用性的理论指导。本文主要研究工作包括：
提出了包含“滑行路径初始规划”、“滑行路由动态指派”、“滑行路由实时更新”三个阶段的滑行路由规划机制，并对各个阶段分别进行场面运行建模和相应的路由规划算法研究，建立了A-SMGCS滑行路由理论。其中，
滑行路径初始规划阶段，在划分场面活动区典型运行单元的基础上，提出了一种场面运行单元扩展赋时库所Petri网(Extended Timed Place Petri Net, ETPPN)，建立了场面ETPPN模型，并给出了基于该模型的滑行路径初始规划方法。场面ETPPN模型库所定义了对应场面单元的管制规则约束，避免了以往活动区节点-路段类模型对管制规则约束描述能力的不足，并引入重构机制实现模型结构的动态调整，实时体现场面运行条件的变化，以支持基于该模型进行初始路径规划的可持续性。然后利用遗传算法并采用ETPPN模型中的变迁激发序列编码染色体，设计了染色体合法性检测与修复算法，以保证所得初始滑行路径的实用性，最终实现滑行路径的初始规划，为航班场面滑行提供多条备选的初始路径。
滑行路由动态指派阶段，提出一种场面运行时间窗约束Petri网（Time Windows ConstraintPetri Net,TWCPN）并用于建立场面TWCPN模型，基于该模型给出了一种滑行路由动态指派方法，实现新加入场面运行航班的滑行路由指派，同时调整其它正在滑行航班的路由。场面TWCPN模型库所定义了对应的单元占用时间窗，可以准确描述航空器滑行对交叉口单元的阶段性占用过程。在该模型基础上，以实现路由规划阶段的冲突避免为目标，设计了模型行为演变算法并求解得到可行滑行路由；然后采用单亲遗传算法，用可行滑行路由编码染色体，以最小化航班滑行成本为目标，求解最优或次优滑行路由并完成滑行路由动态指派，避免了以往基于场面运行运筹学模型一味追求最优解、参数多且求解复杂，难以满足实时场面运行的缺陷。
滑行路由实时更新阶段，分析了场面运行不确定性特征，并提出一种集成场面态势监测的滑行路由实时更新方法，然后依据该方法针对航班滑行轨迹相对于指派路由推迟占用某一场面运行单元的情形，设计了对应的路由更新算法。所给滑行路由实时更新方法，将优化与反馈结合，采用实时获取的场面态势信息来驱动路由更新，并利用针对不同情形设计的路由更新算法完成滑行路由实时更新。在路由更新算法设计时，针对A-SMGCS监测到航班结束对某一场面运行单元的占用，以及A-SMGCS监测到场面运行的各种不确定情形，分别采用常态路由更新算法和非常态路由更新算法进行路由更新，克服了以往每隔一个固定时段才更新滑行路由，难以实时应对场面各种不确定事件的不足。
提出了基于虚拟单元划分和分散协调的冲突监控机制，给出了实现该机制的滑行冲突闭环控制框架，并对框架中的冲突预测与避免、冲突探测与解脱进行实施方案、场面运行建模和控制器设计研究，最终建立了A-SMGCS冲突监控理论。其中，
滑行冲突预测与避免方面，提出了一种基于离散事件监控理论的冲突预测与避免实施方案，并给出了该方案中的场面运行过程离散建模方法，以及对头冲突预测与避免控制器的设计方法。在建模场面运行离散过程时，基于已划分的活动区典型运行单元，采用受控Petri网对其建模得到活动区受控Petri网模型，其控制库所可体现外界对场面运行的控制作用，然后采用航空器后续滑行路径对模型中托肯着色，以描述航空器的滑行意图，从而最终得到场面运行受控着色Petri网模型（Controlled Color Petri Net, CCPN）。进一步基于滑行道CCPN模型提出了航空器最小可控滑行路段的概念，并在与其相关的子模型中，依据面向冲突类型、基于产生式规则的冲突预测与避免控制器设计方法，提出了对头冲突预测与避免控制器设计算法，克服了以往基于路由规划提前避免滑行冲突，难以直接控制场面事件的不足。
滑行冲突探测和解脱方面，提出了一种基于混杂模型的冲突探测与解脱实施方案，并给出了该方案中的场面运行过程混杂建模方法，以及交叉口冲突探测与解脱控制器的设计方法。定义一种扩展混杂Petri网（Extended Hybrid Petri Net, EHPN），建立场面EHPN模型。该模型中控制库所可体现外界对场面运行的控制作用，而定义在一般库所上的外界环境同步事件以及定义在有向弧上的变迁强制使能条件，则实现了对场面运行混杂状态的实时跟踪。基于所建交叉口EHPN模型，设计了交叉口滑行冲突探测与解脱控制器，通过离散性预警条件和连续性预警条件设计，减少虚警和误警出现的概率，并采用交叉口停止排灯来执行控制器决策的冲突解脱指令，可以直接引导飞行员操纵航空器滑行。
Establishing integrated air traffic control system to achieve seamless air traffic control is thestrategic goal for next generation air transportation system. Advanced Surface Movement Guidanceand Control Systems (A-SMGCS) will support seamless operation in airport surface throughmonitoring and control on movement objects (aircrafts and cars). It will play an essential role in thefuture air traffic control system. In the modularize implementation scheme for A-SMGCS, routingfunction model and conflict control function model are key models. The former is in charge ofproviding conflict-free taxi trajectories for movement objects; the latter takes charge in preventingobjects running into conflict situation or colliding with each other. However, past research onA-SMGCS routing and conflict control was mostly for some concrete airport, lacking of research oncorresponding universal theory. In this thesis, human-in-the-loop multilevel hierarchical controlstructure for A-SMGCS was established, and A-SMGCS routing and control were integrated into ahierarchical control structure. The Petri Net theory and analysis method was introduced into theresearch on A-SMGCS routing and control. Corresponding research fruit will provide universal theoryguidance for A-SMGCS implementation. Main research work in this thesis was as following:
Universal A-SMGCS routing mechanism of three stages was proposed, which includes initialtaxi routes planning, dynamic taxi route assignment, and taxi route updating in real-time. For theresearch of each stage, corresponding surface operation modeling methods and routing algorithmswere investigated to form the A-SMGCS routing theory.
On the initial taxi routes planning, based on the surface typical operation zone division, one kindof Extended Timed Place Petri Net (ETPPN) was proposed and used to establish correspondingsurface ETPPN model. The initial taxi routes planning method was provided based on this model.Places in surface ETPPN model was defined using control regulations for its related operation zone,which overcome the disadvantage on control regulations representation in surface node-link model.The reconfiguration principle for structure dynamic adjustment in ETPPN model was proposed,which reflected the change on surface operation condition and supported consistent initial taxi routesplanning based on this model. The Genetic Algorithm (GA) was adopted and transition firingsequences of the ETPPN model were used as chromosomes. In order to ensure the practicability ofinitial taxi routes, algorithm for chromosome validation and amendment was provided. Finally, theinitial taxi routes set of defined number for aircraft taxi on surface was provided.
On the dynamic taxi route assignment, one kind of Time Window Constrained Petri Net(TWCPN) was defined and used to establish the surface TWCPN. One taxi routes assignment methodbased on the TWCPN model was proposed to assign taxi routes for new flight. Meanwhile, routing forcurrently taxiing aircrafts were adjusted. Places in surface TWCPN model was defined using timewindow for its related operation zone, which reflected the dynamic occupation and release foraircrafts in divided operation zone. The state transition algorithm for surface TWCPN model wasprovided, fulfilling conflict avoidance and feasible taxi routes search. And then, Partheno-Geneticalgorithm (PGA) for minimizing the taxi cost was proposed and one new mixed switch and mutationoperator was designed, fulfilling reasonable taxi route search and the dynamic taxi route assignment.The proposed taxi routes assignment method overcome disadvantage of operations model, which settoo many parameters leading complication on computation and can’t meet requirement of real timesurface operation.
On the taxi route updating in real-time, the uncertainties in surface operation was analyzed andone kind of taxi route updating method which integrated surface operation tendency monitoring wasprovide. And also, one concrete taxi routes updating algorithm was proposed for aircraft taxitrajectory postponed occupying one zone comparing to the assigned taxi routes. In the taxi routeupdating method, optimization and feedback mechanism were integrated, and the surface operationtendency was used to drive the update process. And then, this process was fulfilled using concretealgorithms for different scenarios. In concrete taxi routes updating algorithm designing, the regularand non-regular taxi route updating algorithms were provided, which overcome the disadvantage ofpast method updating taxi routs every few minutes and can not tackle surface uncertainties.
Virtual zone division, decentralized and coordinated-based control mechanism was proposed.And also, the corresponding surface conflict feedback control structure was provided, in which, theconflict prediction and avoidance, conflict detection and resolution were investigated fromimplementation scheme, surface operation modeling and controller design, finally forming theA-SMGCS conflict control theory.
On conflict prediction and avoidance, one implementation scheme based on the discrete eventsupervisor theory was proposed, the surface operation process modeling method from discreteperspective was provided, and the controller design method for head-on conflict prediction andavoidance was provide. In surface discrete operation process modeling, the controlled Petri Net modelfor surface movement area was constructed. In this model, the controlled Places could represented thecontrol role from outside, and then the token was colored using the residual taxi route forcorresponding aircraft, which represented the aircraft taxi tendency and finally formed the Controlled Color Petri Net (CCPN) for surface operation. In the surface CCPN model, the least controlled taxisegment for aircrafts was proposed. In its related sub-model, the controller design algorithm forhead-on conflict prediction and avoidance was proposed, according to conflict category oriented andproduction rules-based conflict prediction and avoidance controller design method. The proposedmethod overcomes the disadvantage of routing-based taxi conflict avoidance method which can nottackle surface event directly.
On conflict detection and resolution, one implementation scheme based on hybrid model wasproposed, the surface operation process modeling method from hybrid perspective was provided, andthe controller design method for intersection conflict detection and resolution was provided. One kindof Extended Hybrid Petri Net (EHPN) was defined and used to model surface operation. Thecontrolled Places in surface EHPN could represent control role from outside. Meanwhile, thesynchronizing event defined on ordinary Places and the force enable conditions for transitions couldtrack the surface hybrid state. Based on the intersection EHPN model, the corresponding controller forconflict detection and resolution was designed. The discrete and continuous conflict cautionconditions were proposed to reduce the probability on false alarm and missed alarm. In order todirectly provide visual guidance for pilot, the intersection stop bars were used to execute the conflictresolution command.
提出了包含“滑行路径初始规划”、“滑行路由动态指派”、“滑行路由实时更新”三个阶段的滑行路由规划机制，并对各个阶段分别进行场面运行建模和相应的路由规划算法研究，建立了A-SMGCS滑行路由理论。其中，
滑行路径初始规划阶段，在划分场面活动区典型运行单元的基础上，提出了一种场面运行单元扩展赋时库所Petri网(Extended Timed Place Petri Net, ETPPN)，建立了场面ETPPN模型，并给出了基于该模型的滑行路径初始规划方法。场面ETPPN模型库所定义了对应场面单元的管制规则约束，避免了以往活动区节点-路段类模型对管制规则约束描述能力的不足，并引入重构机制实现模型结构的动态调整，实时体现场面运行条件的变化，以支持基于该模型进行初始路径规划的可持续性。然后利用遗传算法并采用ETPPN模型中的变迁激发序列编码染色体，设计了染色体合法性检测与修复算法，以保证所得初始滑行路径的实用性，最终实现滑行路径的初始规划，为航班场面滑行提供多条备选的初始路径。
滑行路由动态指派阶段，提出一种场面运行时间窗约束Petri网（Time Windows ConstraintPetri Net,TWCPN）并用于建立场面TWCPN模型，基于该模型给出了一种滑行路由动态指派方法，实现新加入场面运行航班的滑行路由指派，同时调整其它正在滑行航班的路由。场面TWCPN模型库所定义了对应的单元占用时间窗，可以准确描述航空器滑行对交叉口单元的阶段性占用过程。在该模型基础上，以实现路由规划阶段的冲突避免为目标，设计了模型行为演变算法并求解得到可行滑行路由；然后采用单亲遗传算法，用可行滑行路由编码染色体，以最小化航班滑行成本为目标，求解最优或次优滑行路由并完成滑行路由动态指派，避免了以往基于场面运行运筹学模型一味追求最优解、参数多且求解复杂，难以满足实时场面运行的缺陷。
滑行路由实时更新阶段，分析了场面运行不确定性特征，并提出一种集成场面态势监测的滑行路由实时更新方法，然后依据该方法针对航班滑行轨迹相对于指派路由推迟占用某一场面运行单元的情形，设计了对应的路由更新算法。所给滑行路由实时更新方法，将优化与反馈结合，采用实时获取的场面态势信息来驱动路由更新，并利用针对不同情形设计的路由更新算法完成滑行路由实时更新。在路由更新算法设计时，针对A-SMGCS监测到航班结束对某一场面运行单元的占用，以及A-SMGCS监测到场面运行的各种不确定情形，分别采用常态路由更新算法和非常态路由更新算法进行路由更新，克服了以往每隔一个固定时段才更新滑行路由，难以实时应对场面各种不确定事件的不足。
提出了基于虚拟单元划分和分散协调的冲突监控机制，给出了实现该机制的滑行冲突闭环控制框架，并对框架中的冲突预测与避免、冲突探测与解脱进行实施方案、场面运行建模和控制器设计研究，最终建立了A-SMGCS冲突监控理论。其中，
滑行冲突预测与避免方面，提出了一种基于离散事件监控理论的冲突预测与避免实施方案，并给出了该方案中的场面运行过程离散建模方法，以及对头冲突预测与避免控制器的设计方法。在建模场面运行离散过程时，基于已划分的活动区典型运行单元，采用受控Petri网对其建模得到活动区受控Petri网模型，其控制库所可体现外界对场面运行的控制作用，然后采用航空器后续滑行路径对模型中托肯着色，以描述航空器的滑行意图，从而最终得到场面运行受控着色Petri网模型（Controlled Color Petri Net, CCPN）。进一步基于滑行道CCPN模型提出了航空器最小可控滑行路段的概念，并在与其相关的子模型中，依据面向冲突类型、基于产生式规则的冲突预测与避免控制器设计方法，提出了对头冲突预测与避免控制器设计算法，克服了以往基于路由规划提前避免滑行冲突，难以直接控制场面事件的不足。
滑行冲突探测和解脱方面，提出了一种基于混杂模型的冲突探测与解脱实施方案，并给出了该方案中的场面运行过程混杂建模方法，以及交叉口冲突探测与解脱控制器的设计方法。定义一种扩展混杂Petri网（Extended Hybrid Petri Net, EHPN），建立场面EHPN模型。该模型中控制库所可体现外界对场面运行的控制作用，而定义在一般库所上的外界环境同步事件以及定义在有向弧上的变迁强制使能条件，则实现了对场面运行混杂状态的实时跟踪。基于所建交叉口EHPN模型，设计了交叉口滑行冲突探测与解脱控制器，通过离散性预警条件和连续性预警条件设计，减少虚警和误警出现的概率，并采用交叉口停止排灯来执行控制器决策的冲突解脱指令，可以直接引导飞行员操纵航空器滑行。
Establishing integrated air traffic control system to achieve seamless air traffic control is thestrategic goal for next generation air transportation system. Advanced Surface Movement Guidanceand Control Systems (A-SMGCS) will support seamless operation in airport surface throughmonitoring and control on movement objects (aircrafts and cars). It will play an essential role in thefuture air traffic control system. In the modularize implementation scheme for A-SMGCS, routingfunction model and conflict control function model are key models. The former is in charge ofproviding conflict-free taxi trajectories for movement objects; the latter takes charge in preventingobjects running into conflict situation or colliding with each other. However, past research onA-SMGCS routing and conflict control was mostly for some concrete airport, lacking of research oncorresponding universal theory. In this thesis, human-in-the-loop multilevel hierarchical controlstructure for A-SMGCS was established, and A-SMGCS routing and control were integrated into ahierarchical control structure. The Petri Net theory and analysis method was introduced into theresearch on A-SMGCS routing and control. Corresponding research fruit will provide universal theoryguidance for A-SMGCS implementation. Main research work in this thesis was as following:
Universal A-SMGCS routing mechanism of three stages was proposed, which includes initialtaxi routes planning, dynamic taxi route assignment, and taxi route updating in real-time. For theresearch of each stage, corresponding surface operation modeling methods and routing algorithmswere investigated to form the A-SMGCS routing theory.
On the initial taxi routes planning, based on the surface typical operation zone division, one kindof Extended Timed Place Petri Net (ETPPN) was proposed and used to establish correspondingsurface ETPPN model. The initial taxi routes planning method was provided based on this model.Places in surface ETPPN model was defined using control regulations for its related operation zone,which overcome the disadvantage on control regulations representation in surface node-link model.The reconfiguration principle for structure dynamic adjustment in ETPPN model was proposed,which reflected the change on surface operation condition and supported consistent initial taxi routesplanning based on this model. The Genetic Algorithm (GA) was adopted and transition firingsequences of the ETPPN model were used as chromosomes. In order to ensure the practicability ofinitial taxi routes, algorithm for chromosome validation and amendment was provided. Finally, theinitial taxi routes set of defined number for aircraft taxi on surface was provided.
On the dynamic taxi route assignment, one kind of Time Window Constrained Petri Net(TWCPN) was defined and used to establish the surface TWCPN. One taxi routes assignment methodbased on the TWCPN model was proposed to assign taxi routes for new flight. Meanwhile, routing forcurrently taxiing aircrafts were adjusted. Places in surface TWCPN model was defined using timewindow for its related operation zone, which reflected the dynamic occupation and release foraircrafts in divided operation zone. The state transition algorithm for surface TWCPN model wasprovided, fulfilling conflict avoidance and feasible taxi routes search. And then, Partheno-Geneticalgorithm (PGA) for minimizing the taxi cost was proposed and one new mixed switch and mutationoperator was designed, fulfilling reasonable taxi route search and the dynamic taxi route assignment.The proposed taxi routes assignment method overcome disadvantage of operations model, which settoo many parameters leading complication on computation and can’t meet requirement of real timesurface operation.
On the taxi route updating in real-time, the uncertainties in surface operation was analyzed andone kind of taxi route updating method which integrated surface operation tendency monitoring wasprovide. And also, one concrete taxi routes updating algorithm was proposed for aircraft taxitrajectory postponed occupying one zone comparing to the assigned taxi routes. In the taxi routeupdating method, optimization and feedback mechanism were integrated, and the surface operationtendency was used to drive the update process. And then, this process was fulfilled using concretealgorithms for different scenarios. In concrete taxi routes updating algorithm designing, the regularand non-regular taxi route updating algorithms were provided, which overcome the disadvantage ofpast method updating taxi routs every few minutes and can not tackle surface uncertainties.
Virtual zone division, decentralized and coordinated-based control mechanism was proposed.And also, the corresponding surface conflict feedback control structure was provided, in which, theconflict prediction and avoidance, conflict detection and resolution were investigated fromimplementation scheme, surface operation modeling and controller design, finally forming theA-SMGCS conflict control theory.
On conflict prediction and avoidance, one implementation scheme based on the discrete eventsupervisor theory was proposed, the surface operation process modeling method from discreteperspective was provided, and the controller design method for head-on conflict prediction andavoidance was provide. In surface discrete operation process modeling, the controlled Petri Net modelfor surface movement area was constructed. In this model, the controlled Places could represented thecontrol role from outside, and then the token was colored using the residual taxi route forcorresponding aircraft, which represented the aircraft taxi tendency and finally formed the Controlled Color Petri Net (CCPN) for surface operation. In the surface CCPN model, the least controlled taxisegment for aircrafts was proposed. In its related sub-model, the controller design algorithm forhead-on conflict prediction and avoidance was proposed, according to conflict category oriented andproduction rules-based conflict prediction and avoidance controller design method. The proposedmethod overcomes the disadvantage of routing-based taxi conflict avoidance method which can nottackle surface event directly.
On conflict detection and resolution, one implementation scheme based on hybrid model wasproposed, the surface operation process modeling method from hybrid perspective was provided, andthe controller design method for intersection conflict detection and resolution was provided. One kindof Extended Hybrid Petri Net (EHPN) was defined and used to model surface operation. Thecontrolled Places in surface EHPN could represent control role from outside. Meanwhile, thesynchronizing event defined on ordinary Places and the force enable conditions for transitions couldtrack the surface hybrid state. Based on the intersection EHPN model, the corresponding controller forconflict detection and resolution was designed. The discrete and continuous conflict cautionconditions were proposed to reduce the probability on false alarm and missed alarm. In order todirectly provide visual guidance for pilot, the intersection stop bars were used to execute the conflictresolution command.
引文
[1]International Civil Aviation Organization (ICAO). Doc.9830-AN/452, Advanced surfacemovement guidance and control systems (A-SMGCS) Manual.2004.
[2] Monzel, F.-G. Demonstration facilities for airport movement management (EFAMM) final report.
[3] Maycroft H. ATOP final report for publication.ATOPS/P/DERA/2000/025, Bedford,2000,
[4] Simpson P, Wall V, Wolfe A. Test Results for Hanburg, Phase2, Operational Benefit Evaluation byTesting A-SMGCS, Qinetiq, Malvem, United Kingdom,2003
[5] Jakobi J., Test Results for Prague, Phase2, Operational Benefit Evaluation by Testing A-SMGCS.DLR, Braunschweig, Germany,2003
[6] Eurocontrol DAP/APT. Definition of A-SMGCS Implementation Levels (Edition1.0)[R]//EATMPInformation Centre, September2003.
[7]Teotino D, Ruggieri M, Nuzzo A. European airport movement management: The Italianchallenge.IEEE Aerospace and Electronic Systems Magazine,2008,23(1):3-12.
[8] Patrick K. Background on single european sky. http://www.sesarju.eu/about/background.2009-7-1.
[9]Lawson,D.R. Surface Movement advisor[J].Journal of air traffic control.1998
[10]Atkins S, Brinton C. Concept Description and Development Plan for the Surface ManagementSystem. Journal of Air Traffic Control,2002,11(1):1-8..
[11]Watnick, M., J. Ianniello, Joseph W. Airport Movement Area Safety System. In Proc. of the11thDigital Avionics Systems Conference, October,1992:549-552.
[12]Foyle, D.C., Andre A.D. Taxiway navigation and situation awareness (T-NASA) system: Problem,design philosophy, and description of an integrated display suite for low-visibility airport surfaceoperations. SAE transactions: Journal of Aerospace,1996,105:1411-1418.
[13]Young, S., and Jones, D. Flight Testing of an Airport Surface Movement Guidance, Navigation,and Control System.Proc. of the Institute of Navigation National Technical Meeting., UnitedStates, January,1998.
[14]]Eric S. Katz, Evaluation of a Prototype Advanced Taxiway Guidance System (ATGS),DOT/FAA/AR-TN00/9, February2000.
[15] Karlin T. What’s NextGen.http://www.jpdo.gov.2011-7-2.
[16]刘鹏飞.“机场综合交通监视与引导系统”应用示范协调会在成都召开http://www.caacsri.com/view.php?tid=2250&cid=68.2011-10-26.
[17]Lu Yu, Liu Changzhong, Wang Zhengning, et al. Multi-sensor data fusion based on environmentdatabase for airport surface surveillance. Proc. Of2011International Conference on Electronicand Optoellectronic.2011, V1-120-V1-123.
[18]邵明珩,章昆,邬秋香. A—SMGCS系统中的助航灯光控制技术浅析.现代电子工程,2009,(3):47-49.
[19]靳学梅,杨恺. A—SMGCS中自动路由规划关键技术研究.现代电子工程,2008,(4):43-45.
[20]严宏,邬秋香,张威. A—SMGCS演示系统实现中有关问题的探讨.现代电子工程,2007,(4):25-28.
[21]张军,罗喜伶,凌明.机场场面监视方法.中国国家专利.2006,200610138111.4:51~20
[22]强成,张学军,吴财军. A-SMGCS中基于QNX平台的车载终端的设计研究.电子技术应用.2006,1:8~11
[23]凌明,张军. A-SMGCS系统动态工作方法.计算机仿真,2007,24(8):57-60.
[24]朱新平,汤新民,韩松臣.基于EHPN的A-SMGCS机场滑行道运行控制建模.交通运输工程学报,2010,10(4):103-108
[25]朱新平,汤新民,韩松臣. A-SMGCS场面运行控制的Petri网建模.武汉理工大学学报（交通科学与工程版）,2011,35(5):950-954.
[26]朱新平,汤新民,韩松臣.基于DES监控理论的滑行道对头冲突控制策略.西南交通大学学报,2011,46(6):64-670.
[27] Tang Xinmin, Wang Yuting, Han Songchen. Aircraft Taxi Route Planning for A-SMGCS basedon Discrete Event Dynamic System modeling. Proc. of the Second International Conference onComputer Modeling and Simulation,2010.
[28] Wang Yuting, Han Songchen, Tang Xinmin, Zhu Xinping. Research on Airport Surface Modelingand Path Planning Algorithm Based on CTPN.2009IEEE International Conference onIntelligent Computing and Intelligent Systems,2009,3:262~266.
[29]朱新平,汤新民,韩松臣. A-SMGCS滑行道交叉口引导灯控制指令决策方法.信息与控制，2010,39（6）:768-773.
[30] Zhu Xinping, Tang Xinmin, Han Songchen. Decision-making method for control of A-SMGCStaxiway centre line lights. Proc. of20103rd International Conference on Computer andElectrical Engineering. Chengdu: IEEE Press,2010:V7-179-V7-183.
[31]Besada, J. A., A. Soto, et al. Design of an A-SMGCS prototype at Barajas airport: Airportsurveillance sensors bias estimation. Proc. of7th International Conference on Information Fusion,2005, Philadelphia,2005:1343-1350.
[32]Garcia, J., J. M. Molina, et al.. Design of an A-SMGCS prototype at Barajas airport: Data fusionalgorithms.Proc. of7th International Conference on Information Fusion,2005. Philadelphia:2005:1335-1342.
[33]Cooffé, C., A. Nelson, et al. Results of the Eurocontrol Sponsored A-SMGCS Ground AssistanceTools for Europe (AGATE) Cost Benefit Analysis (CBA).IEEE,1999:5.D.3-1-5.D.3.23.
[34]Gotteland, J, Durand N. Genetic algorithms applied to airport ground traffic optimization. Proc. ofthe2003Congress on Evolutionary Computation,2003:544-551
[35]Smeltink J W, Soomer M J, Waal P R, Mei R D. An Optimisation Model for Airport TaxiScheduling. Proc. of the INFORMS Annual Meeting, Denver, USA.2004:1-25.
[36]Visser H, Roling P. Optimal airport surface traffic planning using mixed integer linearprogramming. Proc. of AIAA’s3rd Annual Aviation Technology, Integration, and Operations(ATIO) Technology conference. Denver, CO,2003:17-19.
[37]Garcia, J, Berlanga A, Molina JM,et al. Planning techniques for airport ground operations. Proc.of the2002Digital Avionics Systems Conference. IEEE Press,2002:1:1D5-1-1D5-12.
[38]Garcia J, Berlanga A, Molina JM, et al. Optimization of Airport Ground Operations IntegratingGenetic and Dynamic Flow Management Algorithms. AI Communications,2003:1-23.
[39]Garcia, J, Berlanga A, Molina JM, et al. Optimization of Airport Ground Operations IntegratingGenetic and Dynamic Flow Management Algorithms. AI Communication,2005,18(2):1-23.
[40]Keith G, Richards A, Sharma S. Optimization of Taxiway Routing and Runway Scheduling.Proc.of AIAA Guidance, Navigation, and Control Conference and Exhibit, Honolulu.2008:1-11.
[41]Roling P C, Visser H G. Optimal Airport Surface Traffic Planning Using Mixed-Integer LinearProgramming. International Journal of Aerospace Engineering,2008,2008:1-11.
[42]Velthuizen V M. Taxi planning optimization using mixed integer programming. TU Delft, Facultyof Aerospace Engineering,1997.
[43]Marín A, Salmer J. Taxi planner optimization: a management tool.Proc. of the Institution ofMechanical Engineers, Part G: Journal of Aerospace Engineering,2008,222(7):1055-1066.
[44]黄圣国,孙同江,吕兵.运输网络的最短有向路Petri网仿真算法.南京航空航天大学学报,2002,34(2):121-125.
[45]张威,谢晓妤,刘晔.基于Petri网的机场场面路径规划探讨.现代电子工程,2007,4(1):59-61.
[46]汤新民,王玉婷,韩松臣.基于DEDS的A-SMGCS航空器动态滑行路径规划研究.系统工程与电子技术,2010,32(12):2669-2675.
[47]Rathinam, S, Montoya J, Jung Y. An optimization model for reducing aircraft taxi times at theDallas Fort Worth International Airport. Proc. of the26International Congress of theAeronautical Science.2008:1-14.
[48]Ham F V. Development of a Taxi Planning Tool Using Genetic Optimization. Delft AerospaceFaculty of Aerospace Engineering,1999.
[49]Garcia A, Berlanga A, Molina JM, et al. Methods for operations planning in airport decisionsupport systems.Applied Intelligence,2005,22(3):183-206.
[50]Marín á G. Airport management: taxi planning. Annals of Operations Research,2006,143:191-202.
[51]Brinton C, Krozel J, Capozzi B, et al. Improved taxi prediction algorithms for the surfacemanagement system.Proc. of the AIAA Guidance, Navigation, and Control Conference andExhibit. Monterey,2002:1-11.
[52]Lee Hanbong, Balakrishnan H. Optimization of Airport Taxiway Operations at DetroitMetropolitan Airport (DTW).Proc. Of10th Aviation Technology, Integration, andOperation(ATIO) Conference. Texas,2010:1-16.
[53]Balakrishnan H, Jung Y. A Framework for Coordinated Surface Operations Planning atDallas-Fort Worth International Airport.Proc. of AIAA Guidance, Navigation, and ControlConference, Hilton Head, USA.2007:1-19.
[54] Gotteland J, Durand N, Alliot J M, et al. Aircraft ground traffic optimization.Proc. of the Geneticand Evolutionary Computation Conference, San Francisco, USA.2001:1-9.
[55]Gotteland J, Durand N. Handling CFMU slots in busy airports.Proc. of the Air TrafficManagement R&D Seminar,2003.
[56] Durand, N, Gotteland J. Genetic algorithms applied to air traffic management. Metaheuristics forhard optimization,2006,3(1):277-306.
[57] Montoya J, Wood Z, Rathinam S, et al. A Mixed Integer Linear Program for Solving a MultipleRoute Taxi Scheduling Problem.Proc. of AIAA Guidance, Navigation, and Control Conference,Toronto.2010:1-18.
[58]张莹,胡明华,王艳军.航空器机场地面滑行时刻优化模型研究.中国民航飞行学院学报，2006，17(5):3-6.
[59] Clare G, Richards A, Sharma S. Receding Horizon, Iterative Optimization of Taxiway Routingand Runway Scheduling.Proc. of the AIAA Guidance, Navigation, and Control Conference,Chicago.2009:1-14.
[60] Marín A, Codina E. Network design: taxi planning.Annals of Operations Research,2008,157(1):135-151.
[61] Marín A. Decomposition methodology to solve taxi planning.Proc. of the11th Meeting of theEuropean Working Group on Transportation, Bari,2006:27-29.
[62]虞秀兰,程朋,施锋.Gate-to-Gate模式下航班到达的综合调度.系统仿真学报,2010,22(增刊1)：182-186.
[63] Holland J. Adaptation in Natural and artificial systems: The University of Michigan Press, USA,second edition.1992.
[64] Daniel D, Alliot J, Schoenauer M, et al, Genetic algortithms for air traffic assignment.Proc. of the11th European Conference on artificial intelligence Applications, Amsterdam,1994:8-16.
[65] Oussedik S, Delahaye D. Reducing air traffic congestion by genetic algorithm.Lecture Notes inComputer Science,1498(3):855-864.
[66] Giannzaa D, Alliot J. Optimization of air traffic control sector configurations using tree searchmethods and genetic algorithms.Proc. of the21st Digital Avionics systems conference, Irvine,2002:2A5-1-2A5-8.
[67]Durand N, Alliot J, Medioni F. Neural Nets trained by genetic algorithms for collision avoidanceApplied artficl interlligence.2000,13(3):205-213.
[68] Pesic B, Durand N. Aircraft ground traffic optimization using a genetic algorithm.Proc. of theGenetic and Evolutionary Computation Conference, San Francisco, USA.2001:1-9.
[69]刘长有,丛晓东.基于遗传算法的飞机滑行路径优化.交通信息与安全,2009,27(3):6-8.
[70] LIU Changyou, GUO Kaifeng. Aircraft Taxiing Scheduling Optimization Based on GeneticAlgorithm.Proc. of2nd International Conference on Information Engineering and ComputerScience.2010:1-4.
[71]刘兆明,葛宏伟,钱锋.基于遗传算法的机场调度优化算法.华东理工大学学报(自然科学版),2008,34(3):392-398.
[72] LI Zhen, ZHANG Jun, ZHANG Xuejun. A Dynamic Model for Aircraft Route Optimizing inAirport Surface Management.Proc. of the9th International Conference on ElectronicMeasurement and Instruments, Beijing,2009:3-1068-3-1072.
[73]陈世林,胡明华,张洪海. SMS中基于冲突探测的滑行道轨迹预测算法研究.四川大学学报(自然科学版),2008,45(6):1357-1361.
[74]王艳军,胡明华,苏炜.基于冲突回避的动态滑行路径算法.西南交通大学学报,2009,44(6):933-939.
[75]靳学梅,陈培英.改进的Dijkstra算法在机场场面路由规划中的应用.现代电子工程,2009,(3):40-43.
[76]尤杰,韩松臣.基于多Agent的机场场面最优滑行路径算法.交通运输工程学报,2009,9(1):109-112.
[77]Lyon, Ervin F, Airport Surface Traffic Automation, Lincoln Laboratory Journal,1995,4(2):151-188.
[78]Harald Wihelmsen. Preventing runway conflicts: the role of airport surveillance, tower-cab alerts,and runway-status lights. The Lincoln laboratory Journal,1994.
[79]Honywell International Inc.,2006,Runway awareness and advisory system (RAAS),ProductDescription.
[80]Evans, Brian,2007,In-trail,on-time,avionics magazine, June1,2007
[81]Jones, D.R. and L. J.Prinzel. Runway Incursion Prevention for General Aviation Operations.Proc.of the25th Digital Avionics Systems Conference. IEEE Press,2006:3D4-1-3D4-12.
[82]Young S D, Jones D R. Runway incursion prevention: A technology solution.Proc. of the54thAnnual International Air Safety Seminar, Athens.2001:221-238.
[83]Green, D. Runway safety monitor algorithm for runway incursion detection and alerting.NASA/CR-2002-211416, Washington D.C.: National Aeronautics and Space Administration,2002.
[84]高强，唐小卫，朱金福.停机区推出共用停止点设计优化.交通信息与安全,2009,27(6):156-160.
[85]CHENG Y. Solving push-out conflicts in apron taxiways of airports by a network-basedsimulation. Computers Industrial Engineering,1998,34(2):351-369.
[86]Pitfield, D, Brooke A, Jerrard E A. A Monte-Carlo simulation of potentially conflicting groundmovements at a new international airport. Journal of Air Transport Management，1998,4(1):3-9.
[87] Cheng V. H. L., Sharma V. A study of aircraft taxi performance for enhancing airport surfacetraffic control. IEEE Transactions on Intelligent Transportation Systems,2001,2(2):39-54.
[88] Hollisterm W.M. Airport surface traffic automation study.Department of Transportation,Washington, D.C.20591
[89]Ianniello, Joseph W., Kruczek Raymond M. Airport surface collision warning systemimplementation. In Proc. of the11th Digital Avionics Systems Conference, October,1993:742-746.
[90] Piazza E. A-SMGCS routing and guidance functions. IEEE Aerospace and Electronic SystemsMagazine.2000,15(11):34-34.
[91] TANG Xinmin. Petri Net Controller Synthesis for Advanced Surface Movement Guidance andControl System. In Proc. of the IEEE International conference on Information andAutomation.2009:483-488.
[92] Garcia, J., J. Besada. Data processing techniques for conflict detection on airport surface[C].InProc. of the5th USA/Europe ATM R&D Seminar, Budepest, Hungray,2003.
[93] Jones D., Prinzel L., Otero SD, et al. Collision avoidance for airport traffic conceptevaluation.Proc. Of Ditital Avionics Systems Conference,2009:4.C.4-1-4.C.4-15.
[94] Green, D., Otero SD., Barker, GD, et al. Initial Concept for Terminal Area Conflict Detection,Alerting, and Resolution Capability on or Near the Airport Surface.NASA/TM-2009-215696,Washington D.C.: National Aeronautics and Space Administration,2002.
[95] Jones D., Prinzel LJ, Shelton KJ, et al. Collision avoidance for airport traffic simulationevaluation.Proc. Of29th IEEE/AOAA Digital Avionics Systems Conference. IEEE Press,2010:3.B.1-1-3.B.1-15.
[96] EAST S. Sensis to develop advanced ground conflict detection and resolution algorithm forNASA.http://www.sensis.com/docs/871/,2010,10,25/2011.11.18.
[97] Teutsch J, Mollwitz V. Virtual block control and separation bubbles in ATC low visibilityoperations.Integrated Communications, Navigation and Surveillance Conference. Arlington:IEEE Press,2009:1-17.
[98] Mollwitz V, Schaik FJ, Teutsch J. virtual block control and separation bubbles evaluation incockpit simulator trails.NLR-TP-2009-383, Amsterdam: National Aerospace Laboratory NLR,2009.
[99] Molina JM., Garcia J, Besada JA, et al. Design of an A-SMGCS prototype at Barajas airport:available information and architecture.Proc. Of the20058th International Conference onInformation Fusion (FUSION),2005:1327-1334.
[100]Mario, C., Rife J. Integrity and continuity for automated surface conflict-detectionmonitoring.Porc. Of2011Integrated Communication, Navigation and Surveillance Conference.Herndon, IEEE Press,2011:I3-1-I3-12.
[101] Pepitone D., Tomaszewski E. Method and systems for alerting an aircraft crew member of apotential conflict between aircraft on a taxiway. USA: US7962279,2011.
[102]Pestana G., CASACA A, Silva T, et al. Monitoring Safety Hazard Situations in an AirportEnvironment.Proc. Of the International Conference on Communication, Computer and Power.Muscat, IEEE Press,2007:19-21.
[103] Brinton C R. Local Data Exchange for Airport Surface Trajectory-Based Operations.Proc. ofInternational Conference, Navigation, and Surveillance, Honolulu.2008:1-8.
[104]Krozel J., Peters M. Strategic conflict detection and resolution for free flight.Proc. Of the36thconference on decision and control. San Diego, California, IEEE Press,1997:1822-1828.
[105]董利达.基于Petri网的离散事件监控理论[博士学位论文],浙江：浙江大学，2004.
[106] Carotenuto, S. State of the art in A-SMGCS. Germany: European commission,2005.
[107] Atkin J, Burke E, Ravizza S. The Airport Ground Movement Problem: Past and CurrentResearch and Future Directions.Proc. of the4th International Conference on Research in AirTransportation. Budapest,2010:131-138.
[108]王化冰.一种基于同步合成Petri网的FMS建模方法.系统工程理论与实践.2001,(2):35-42.
[109]Lorens, M., Oliver J. Structural and dynamic changes in concurrent systems: Reconfigurablepetri nets. IEEE Transactions on Computers,2004,53(9):1147-1158.
[110]GEN M, CHENG R W. Genetic algorithms and engineering optimization. N.Y., USA:JohnWiley and Sons,2000.
[111]李茂军,朱陶业,童调生.单亲遗传算法与传统遗传算法的比较研究.系统工程,2001,19(1):61-65.
[112]李茂军,童调生.单亲遗传算法及其全局收敛性分析.自动化学报,1999.25(1):68-72.
[113]熊杰,张晨.基于飞机滑行油耗的枢纽机场机位分配研究.交通运输工程与信息,2010,10(3):165-170.
[114]徐肖豪,李雄.航班地面等待模型中的延误成本分析与仿真.南京航空航天大学学报,2006,38(1):115~120.
[115]Atkins, S., C. Brinton, Yoon Jung. Implication of Variability in Airport Surface Operations on4-D Trajectory Planning. Proc. Of26th Congress of International Council of the AeronauticalScience, Alaska,2008:1-17.
[116]Brinton C., Atkins S.Analysis of Taxi Conformance Monitoring Algorithms and Performance.Proc. Of the Integrated Communicatioins, Navigation and Surveillance Conference, Herndon,2007:1-8.
[117]Zheng, Q, Zhao YY, Capozzi B.Time-of-Arrival Based Taxi Conformance Monitoring forSurface Operation.Porc. of AIAA Guidance, Navigation, and Control Conference, Toronto,2010:1-27.
[118]Zheng QM, Zhao YY, Capozzi, B.Taxi route conformance monitoring for surface operations.Proc. of the2011Integrated Communication, Navigation and Surveillance Conference. Herndon,IEEE Press,2011:1-28
[119]Mann, G, I. Hwang.4D Aircraft Taxiway Conformance Monitoring with Stochastic LinearHybrid Systems.Proc. Of AIAA Guidance, Navigation, and Control Conference,2011:1-15.
[120]Capozzi, B J, DiFelici J. Towards Automated Airport Surface Traffic Control: Potential Benefitsand Feasibility.Proc. of AIAA Guidance, Navigation, and Control Conference and Exhibit.Providence, RI,2004:1-16.
[121]Werther B. Colored Petri net based modeling of airport control processes. Proc. of Internationalconference on Computational Intelligence for Modelling, Control and Automation, CIMCA.Sydney,2006:1-6.
[122]Werther B, Moehlenbrink C, Rudolph, M. Colored Petri Net Based Formal Airport ControlModel for Simulation and Analysis of Airport Control Processes. Lecture Notes in ComputerScience4561,2007:1027-1036.
[123]秦瑛.机场终端区作业的离散事件系统建模与优化[硕士学位论文],天津：中国民航大学，2006.
[124]Demael, J J, Levis A H. On the generation of a variable structure airport surface traffic controlsystem.Proc. Of IEEE International Symposium on Intelligent Control. Tallinn, IEEE Press,1989:74-81.
[125]黄圣国,肖靖.基于Petri网的空中交通管制辅助决策系统.南京航空航天大学学报,2000,32(4):206-211.
[126]罗继亮,邹慧莉.基于Petri网的车辆交通实时调度研究.系统仿真学报2007,19(1):148-150.
[127]吴立辉,张洁.基于多代理的知识有色赋时Petri网的晶圆制造系统建模方法.计算机集成制造系统.2009,15(10):1922-1929.
[128]Shakarian A, Haraldsdottir A. Required total system performance and results of a short termconflict alert simulation study.Proc. of4th US/Europe Air Traffic Management R&D Seminar,Santa Fe, IEEE Press,2001:1-9.
[129]李惠峰,周锐.混合Petri网及其可达性分析.北京航空航天大学学报,2000,26(2):149-152.
[130]邵明珩,章昆,邬秋香. A—SMGCS系统中的助航灯光控制技术浅析.现代电子工程,2009,(3):47-49.
[2] Monzel, F.-G. Demonstration facilities for airport movement management (EFAMM) final report.
[3] Maycroft H. ATOP final report for publication.ATOPS/P/DERA/2000/025, Bedford,2000,
[4] Simpson P, Wall V, Wolfe A. Test Results for Hanburg, Phase2, Operational Benefit Evaluation byTesting A-SMGCS, Qinetiq, Malvem, United Kingdom,2003
[5] Jakobi J., Test Results for Prague, Phase2, Operational Benefit Evaluation by Testing A-SMGCS.DLR, Braunschweig, Germany,2003
[6] Eurocontrol DAP/APT. Definition of A-SMGCS Implementation Levels (Edition1.0)[R]//EATMPInformation Centre, September2003.
[7]Teotino D, Ruggieri M, Nuzzo A. European airport movement management: The Italianchallenge.IEEE Aerospace and Electronic Systems Magazine,2008,23(1):3-12.
[8] Patrick K. Background on single european sky. http://www.sesarju.eu/about/background.2009-7-1.
[9]Lawson,D.R. Surface Movement advisor[J].Journal of air traffic control.1998
[10]Atkins S, Brinton C. Concept Description and Development Plan for the Surface ManagementSystem. Journal of Air Traffic Control,2002,11(1):1-8..
[11]Watnick, M., J. Ianniello, Joseph W. Airport Movement Area Safety System. In Proc. of the11thDigital Avionics Systems Conference, October,1992:549-552.
[12]Foyle, D.C., Andre A.D. Taxiway navigation and situation awareness (T-NASA) system: Problem,design philosophy, and description of an integrated display suite for low-visibility airport surfaceoperations. SAE transactions: Journal of Aerospace,1996,105:1411-1418.
[13]Young, S., and Jones, D. Flight Testing of an Airport Surface Movement Guidance, Navigation,and Control System.Proc. of the Institute of Navigation National Technical Meeting., UnitedStates, January,1998.
[14]]Eric S. Katz, Evaluation of a Prototype Advanced Taxiway Guidance System (ATGS),DOT/FAA/AR-TN00/9, February2000.
[15] Karlin T. What’s NextGen.http://www.jpdo.gov.2011-7-2.
[16]刘鹏飞.“机场综合交通监视与引导系统”应用示范协调会在成都召开http://www.caacsri.com/view.php?tid=2250&cid=68.2011-10-26.
[17]Lu Yu, Liu Changzhong, Wang Zhengning, et al. Multi-sensor data fusion based on environmentdatabase for airport surface surveillance. Proc. Of2011International Conference on Electronicand Optoellectronic.2011, V1-120-V1-123.
[18]邵明珩,章昆,邬秋香. A—SMGCS系统中的助航灯光控制技术浅析.现代电子工程,2009,(3):47-49.
[19]靳学梅,杨恺. A—SMGCS中自动路由规划关键技术研究.现代电子工程,2008,(4):43-45.
[20]严宏,邬秋香,张威. A—SMGCS演示系统实现中有关问题的探讨.现代电子工程,2007,(4):25-28.
[21]张军,罗喜伶,凌明.机场场面监视方法.中国国家专利.2006,200610138111.4:51~20
[22]强成,张学军,吴财军. A-SMGCS中基于QNX平台的车载终端的设计研究.电子技术应用.2006,1:8~11
[23]凌明,张军. A-SMGCS系统动态工作方法.计算机仿真,2007,24(8):57-60.
[24]朱新平,汤新民,韩松臣.基于EHPN的A-SMGCS机场滑行道运行控制建模.交通运输工程学报,2010,10(4):103-108
[25]朱新平,汤新民,韩松臣. A-SMGCS场面运行控制的Petri网建模.武汉理工大学学报（交通科学与工程版）,2011,35(5):950-954.
[26]朱新平,汤新民,韩松臣.基于DES监控理论的滑行道对头冲突控制策略.西南交通大学学报,2011,46(6):64-670.
[27] Tang Xinmin, Wang Yuting, Han Songchen. Aircraft Taxi Route Planning for A-SMGCS basedon Discrete Event Dynamic System modeling. Proc. of the Second International Conference onComputer Modeling and Simulation,2010.
[28] Wang Yuting, Han Songchen, Tang Xinmin, Zhu Xinping. Research on Airport Surface Modelingand Path Planning Algorithm Based on CTPN.2009IEEE International Conference onIntelligent Computing and Intelligent Systems,2009,3:262~266.
[29]朱新平,汤新民,韩松臣. A-SMGCS滑行道交叉口引导灯控制指令决策方法.信息与控制，2010,39（6）:768-773.
[30] Zhu Xinping, Tang Xinmin, Han Songchen. Decision-making method for control of A-SMGCStaxiway centre line lights. Proc. of20103rd International Conference on Computer andElectrical Engineering. Chengdu: IEEE Press,2010:V7-179-V7-183.
[31]Besada, J. A., A. Soto, et al. Design of an A-SMGCS prototype at Barajas airport: Airportsurveillance sensors bias estimation. Proc. of7th International Conference on Information Fusion,2005, Philadelphia,2005:1343-1350.
[32]Garcia, J., J. M. Molina, et al.. Design of an A-SMGCS prototype at Barajas airport: Data fusionalgorithms.Proc. of7th International Conference on Information Fusion,2005. Philadelphia:2005:1335-1342.
[33]Cooffé, C., A. Nelson, et al. Results of the Eurocontrol Sponsored A-SMGCS Ground AssistanceTools for Europe (AGATE) Cost Benefit Analysis (CBA).IEEE,1999:5.D.3-1-5.D.3.23.
[34]Gotteland, J, Durand N. Genetic algorithms applied to airport ground traffic optimization. Proc. ofthe2003Congress on Evolutionary Computation,2003:544-551
[35]Smeltink J W, Soomer M J, Waal P R, Mei R D. An Optimisation Model for Airport TaxiScheduling. Proc. of the INFORMS Annual Meeting, Denver, USA.2004:1-25.
[36]Visser H, Roling P. Optimal airport surface traffic planning using mixed integer linearprogramming. Proc. of AIAA’s3rd Annual Aviation Technology, Integration, and Operations(ATIO) Technology conference. Denver, CO,2003:17-19.
[37]Garcia, J, Berlanga A, Molina JM,et al. Planning techniques for airport ground operations. Proc.of the2002Digital Avionics Systems Conference. IEEE Press,2002:1:1D5-1-1D5-12.
[38]Garcia J, Berlanga A, Molina JM, et al. Optimization of Airport Ground Operations IntegratingGenetic and Dynamic Flow Management Algorithms. AI Communications,2003:1-23.
[39]Garcia, J, Berlanga A, Molina JM, et al. Optimization of Airport Ground Operations IntegratingGenetic and Dynamic Flow Management Algorithms. AI Communication,2005,18(2):1-23.
[40]Keith G, Richards A, Sharma S. Optimization of Taxiway Routing and Runway Scheduling.Proc.of AIAA Guidance, Navigation, and Control Conference and Exhibit, Honolulu.2008:1-11.
[41]Roling P C, Visser H G. Optimal Airport Surface Traffic Planning Using Mixed-Integer LinearProgramming. International Journal of Aerospace Engineering,2008,2008:1-11.
[42]Velthuizen V M. Taxi planning optimization using mixed integer programming. TU Delft, Facultyof Aerospace Engineering,1997.
[43]Marín A, Salmer J. Taxi planner optimization: a management tool.Proc. of the Institution ofMechanical Engineers, Part G: Journal of Aerospace Engineering,2008,222(7):1055-1066.
[44]黄圣国,孙同江,吕兵.运输网络的最短有向路Petri网仿真算法.南京航空航天大学学报,2002,34(2):121-125.
[45]张威,谢晓妤,刘晔.基于Petri网的机场场面路径规划探讨.现代电子工程,2007,4(1):59-61.
[46]汤新民,王玉婷,韩松臣.基于DEDS的A-SMGCS航空器动态滑行路径规划研究.系统工程与电子技术,2010,32(12):2669-2675.
[47]Rathinam, S, Montoya J, Jung Y. An optimization model for reducing aircraft taxi times at theDallas Fort Worth International Airport. Proc. of the26International Congress of theAeronautical Science.2008:1-14.
[48]Ham F V. Development of a Taxi Planning Tool Using Genetic Optimization. Delft AerospaceFaculty of Aerospace Engineering,1999.
[49]Garcia A, Berlanga A, Molina JM, et al. Methods for operations planning in airport decisionsupport systems.Applied Intelligence,2005,22(3):183-206.
[50]Marín á G. Airport management: taxi planning. Annals of Operations Research,2006,143:191-202.
[51]Brinton C, Krozel J, Capozzi B, et al. Improved taxi prediction algorithms for the surfacemanagement system.Proc. of the AIAA Guidance, Navigation, and Control Conference andExhibit. Monterey,2002:1-11.
[52]Lee Hanbong, Balakrishnan H. Optimization of Airport Taxiway Operations at DetroitMetropolitan Airport (DTW).Proc. Of10th Aviation Technology, Integration, andOperation(ATIO) Conference. Texas,2010:1-16.
[53]Balakrishnan H, Jung Y. A Framework for Coordinated Surface Operations Planning atDallas-Fort Worth International Airport.Proc. of AIAA Guidance, Navigation, and ControlConference, Hilton Head, USA.2007:1-19.
[54] Gotteland J, Durand N, Alliot J M, et al. Aircraft ground traffic optimization.Proc. of the Geneticand Evolutionary Computation Conference, San Francisco, USA.2001:1-9.
[55]Gotteland J, Durand N. Handling CFMU slots in busy airports.Proc. of the Air TrafficManagement R&D Seminar,2003.
[56] Durand, N, Gotteland J. Genetic algorithms applied to air traffic management. Metaheuristics forhard optimization,2006,3(1):277-306.
[57] Montoya J, Wood Z, Rathinam S, et al. A Mixed Integer Linear Program for Solving a MultipleRoute Taxi Scheduling Problem.Proc. of AIAA Guidance, Navigation, and Control Conference,Toronto.2010:1-18.
[58]张莹,胡明华,王艳军.航空器机场地面滑行时刻优化模型研究.中国民航飞行学院学报，2006，17(5):3-6.
[59] Clare G, Richards A, Sharma S. Receding Horizon, Iterative Optimization of Taxiway Routingand Runway Scheduling.Proc. of the AIAA Guidance, Navigation, and Control Conference,Chicago.2009:1-14.
[60] Marín A, Codina E. Network design: taxi planning.Annals of Operations Research,2008,157(1):135-151.
[61] Marín A. Decomposition methodology to solve taxi planning.Proc. of the11th Meeting of theEuropean Working Group on Transportation, Bari,2006:27-29.
[62]虞秀兰,程朋,施锋.Gate-to-Gate模式下航班到达的综合调度.系统仿真学报,2010,22(增刊1)：182-186.
[63] Holland J. Adaptation in Natural and artificial systems: The University of Michigan Press, USA,second edition.1992.
[64] Daniel D, Alliot J, Schoenauer M, et al, Genetic algortithms for air traffic assignment.Proc. of the11th European Conference on artificial intelligence Applications, Amsterdam,1994:8-16.
[65] Oussedik S, Delahaye D. Reducing air traffic congestion by genetic algorithm.Lecture Notes inComputer Science,1498(3):855-864.
[66] Giannzaa D, Alliot J. Optimization of air traffic control sector configurations using tree searchmethods and genetic algorithms.Proc. of the21st Digital Avionics systems conference, Irvine,2002:2A5-1-2A5-8.
[67]Durand N, Alliot J, Medioni F. Neural Nets trained by genetic algorithms for collision avoidanceApplied artficl interlligence.2000,13(3):205-213.
[68] Pesic B, Durand N. Aircraft ground traffic optimization using a genetic algorithm.Proc. of theGenetic and Evolutionary Computation Conference, San Francisco, USA.2001:1-9.
[69]刘长有,丛晓东.基于遗传算法的飞机滑行路径优化.交通信息与安全,2009,27(3):6-8.
[70] LIU Changyou, GUO Kaifeng. Aircraft Taxiing Scheduling Optimization Based on GeneticAlgorithm.Proc. of2nd International Conference on Information Engineering and ComputerScience.2010:1-4.
[71]刘兆明,葛宏伟,钱锋.基于遗传算法的机场调度优化算法.华东理工大学学报(自然科学版),2008,34(3):392-398.
[72] LI Zhen, ZHANG Jun, ZHANG Xuejun. A Dynamic Model for Aircraft Route Optimizing inAirport Surface Management.Proc. of the9th International Conference on ElectronicMeasurement and Instruments, Beijing,2009:3-1068-3-1072.
[73]陈世林,胡明华,张洪海. SMS中基于冲突探测的滑行道轨迹预测算法研究.四川大学学报(自然科学版),2008,45(6):1357-1361.
[74]王艳军,胡明华,苏炜.基于冲突回避的动态滑行路径算法.西南交通大学学报,2009,44(6):933-939.
[75]靳学梅,陈培英.改进的Dijkstra算法在机场场面路由规划中的应用.现代电子工程,2009,(3):40-43.
[76]尤杰,韩松臣.基于多Agent的机场场面最优滑行路径算法.交通运输工程学报,2009,9(1):109-112.
[77]Lyon, Ervin F, Airport Surface Traffic Automation, Lincoln Laboratory Journal,1995,4(2):151-188.
[78]Harald Wihelmsen. Preventing runway conflicts: the role of airport surveillance, tower-cab alerts,and runway-status lights. The Lincoln laboratory Journal,1994.
[79]Honywell International Inc.,2006,Runway awareness and advisory system (RAAS),ProductDescription.
[80]Evans, Brian,2007,In-trail,on-time,avionics magazine, June1,2007
[81]Jones, D.R. and L. J.Prinzel. Runway Incursion Prevention for General Aviation Operations.Proc.of the25th Digital Avionics Systems Conference. IEEE Press,2006:3D4-1-3D4-12.
[82]Young S D, Jones D R. Runway incursion prevention: A technology solution.Proc. of the54thAnnual International Air Safety Seminar, Athens.2001:221-238.
[83]Green, D. Runway safety monitor algorithm for runway incursion detection and alerting.NASA/CR-2002-211416, Washington D.C.: National Aeronautics and Space Administration,2002.
[84]高强，唐小卫，朱金福.停机区推出共用停止点设计优化.交通信息与安全,2009,27(6):156-160.
[85]CHENG Y. Solving push-out conflicts in apron taxiways of airports by a network-basedsimulation. Computers Industrial Engineering,1998,34(2):351-369.
[86]Pitfield, D, Brooke A, Jerrard E A. A Monte-Carlo simulation of potentially conflicting groundmovements at a new international airport. Journal of Air Transport Management，1998,4(1):3-9.
[87] Cheng V. H. L., Sharma V. A study of aircraft taxi performance for enhancing airport surfacetraffic control. IEEE Transactions on Intelligent Transportation Systems,2001,2(2):39-54.
[88] Hollisterm W.M. Airport surface traffic automation study.Department of Transportation,Washington, D.C.20591
[89]Ianniello, Joseph W., Kruczek Raymond M. Airport surface collision warning systemimplementation. In Proc. of the11th Digital Avionics Systems Conference, October,1993:742-746.
[90] Piazza E. A-SMGCS routing and guidance functions. IEEE Aerospace and Electronic SystemsMagazine.2000,15(11):34-34.
[91] TANG Xinmin. Petri Net Controller Synthesis for Advanced Surface Movement Guidance andControl System. In Proc. of the IEEE International conference on Information andAutomation.2009:483-488.
[92] Garcia, J., J. Besada. Data processing techniques for conflict detection on airport surface[C].InProc. of the5th USA/Europe ATM R&D Seminar, Budepest, Hungray,2003.
[93] Jones D., Prinzel L., Otero SD, et al. Collision avoidance for airport traffic conceptevaluation.Proc. Of Ditital Avionics Systems Conference,2009:4.C.4-1-4.C.4-15.
[94] Green, D., Otero SD., Barker, GD, et al. Initial Concept for Terminal Area Conflict Detection,Alerting, and Resolution Capability on or Near the Airport Surface.NASA/TM-2009-215696,Washington D.C.: National Aeronautics and Space Administration,2002.
[95] Jones D., Prinzel LJ, Shelton KJ, et al. Collision avoidance for airport traffic simulationevaluation.Proc. Of29th IEEE/AOAA Digital Avionics Systems Conference. IEEE Press,2010:3.B.1-1-3.B.1-15.
[96] EAST S. Sensis to develop advanced ground conflict detection and resolution algorithm forNASA.http://www.sensis.com/docs/871/,2010,10,25/2011.11.18.
[97] Teutsch J, Mollwitz V. Virtual block control and separation bubbles in ATC low visibilityoperations.Integrated Communications, Navigation and Surveillance Conference. Arlington:IEEE Press,2009:1-17.
[98] Mollwitz V, Schaik FJ, Teutsch J. virtual block control and separation bubbles evaluation incockpit simulator trails.NLR-TP-2009-383, Amsterdam: National Aerospace Laboratory NLR,2009.
[99] Molina JM., Garcia J, Besada JA, et al. Design of an A-SMGCS prototype at Barajas airport:available information and architecture.Proc. Of the20058th International Conference onInformation Fusion (FUSION),2005:1327-1334.
[100]Mario, C., Rife J. Integrity and continuity for automated surface conflict-detectionmonitoring.Porc. Of2011Integrated Communication, Navigation and Surveillance Conference.Herndon, IEEE Press,2011:I3-1-I3-12.
[101] Pepitone D., Tomaszewski E. Method and systems for alerting an aircraft crew member of apotential conflict between aircraft on a taxiway. USA: US7962279,2011.
[102]Pestana G., CASACA A, Silva T, et al. Monitoring Safety Hazard Situations in an AirportEnvironment.Proc. Of the International Conference on Communication, Computer and Power.Muscat, IEEE Press,2007:19-21.
[103] Brinton C R. Local Data Exchange for Airport Surface Trajectory-Based Operations.Proc. ofInternational Conference, Navigation, and Surveillance, Honolulu.2008:1-8.
[104]Krozel J., Peters M. Strategic conflict detection and resolution for free flight.Proc. Of the36thconference on decision and control. San Diego, California, IEEE Press,1997:1822-1828.
[105]董利达.基于Petri网的离散事件监控理论[博士学位论文],浙江：浙江大学，2004.
[106] Carotenuto, S. State of the art in A-SMGCS. Germany: European commission,2005.
[107] Atkin J, Burke E, Ravizza S. The Airport Ground Movement Problem: Past and CurrentResearch and Future Directions.Proc. of the4th International Conference on Research in AirTransportation. Budapest,2010:131-138.
[108]王化冰.一种基于同步合成Petri网的FMS建模方法.系统工程理论与实践.2001,(2):35-42.
[109]Lorens, M., Oliver J. Structural and dynamic changes in concurrent systems: Reconfigurablepetri nets. IEEE Transactions on Computers,2004,53(9):1147-1158.
[110]GEN M, CHENG R W. Genetic algorithms and engineering optimization. N.Y., USA:JohnWiley and Sons,2000.
[111]李茂军,朱陶业,童调生.单亲遗传算法与传统遗传算法的比较研究.系统工程,2001,19(1):61-65.
[112]李茂军,童调生.单亲遗传算法及其全局收敛性分析.自动化学报,1999.25(1):68-72.
[113]熊杰,张晨.基于飞机滑行油耗的枢纽机场机位分配研究.交通运输工程与信息,2010,10(3):165-170.
[114]徐肖豪,李雄.航班地面等待模型中的延误成本分析与仿真.南京航空航天大学学报,2006,38(1):115~120.
[115]Atkins, S., C. Brinton, Yoon Jung. Implication of Variability in Airport Surface Operations on4-D Trajectory Planning. Proc. Of26th Congress of International Council of the AeronauticalScience, Alaska,2008:1-17.
[116]Brinton C., Atkins S.Analysis of Taxi Conformance Monitoring Algorithms and Performance.Proc. Of the Integrated Communicatioins, Navigation and Surveillance Conference, Herndon,2007:1-8.
[117]Zheng, Q, Zhao YY, Capozzi B.Time-of-Arrival Based Taxi Conformance Monitoring forSurface Operation.Porc. of AIAA Guidance, Navigation, and Control Conference, Toronto,2010:1-27.
[118]Zheng QM, Zhao YY, Capozzi, B.Taxi route conformance monitoring for surface operations.Proc. of the2011Integrated Communication, Navigation and Surveillance Conference. Herndon,IEEE Press,2011:1-28
[119]Mann, G, I. Hwang.4D Aircraft Taxiway Conformance Monitoring with Stochastic LinearHybrid Systems.Proc. Of AIAA Guidance, Navigation, and Control Conference,2011:1-15.
[120]Capozzi, B J, DiFelici J. Towards Automated Airport Surface Traffic Control: Potential Benefitsand Feasibility.Proc. of AIAA Guidance, Navigation, and Control Conference and Exhibit.Providence, RI,2004:1-16.
[121]Werther B. Colored Petri net based modeling of airport control processes. Proc. of Internationalconference on Computational Intelligence for Modelling, Control and Automation, CIMCA.Sydney,2006:1-6.
[122]Werther B, Moehlenbrink C, Rudolph, M. Colored Petri Net Based Formal Airport ControlModel for Simulation and Analysis of Airport Control Processes. Lecture Notes in ComputerScience4561,2007:1027-1036.
[123]秦瑛.机场终端区作业的离散事件系统建模与优化[硕士学位论文],天津：中国民航大学，2006.
[124]Demael, J J, Levis A H. On the generation of a variable structure airport surface traffic controlsystem.Proc. Of IEEE International Symposium on Intelligent Control. Tallinn, IEEE Press,1989:74-81.
[125]黄圣国,肖靖.基于Petri网的空中交通管制辅助决策系统.南京航空航天大学学报,2000,32(4):206-211.
[126]罗继亮,邹慧莉.基于Petri网的车辆交通实时调度研究.系统仿真学报2007,19(1):148-150.
[127]吴立辉,张洁.基于多代理的知识有色赋时Petri网的晶圆制造系统建模方法.计算机集成制造系统.2009,15(10):1922-1929.
[128]Shakarian A, Haraldsdottir A. Required total system performance and results of a short termconflict alert simulation study.Proc. of4th US/Europe Air Traffic Management R&D Seminar,Santa Fe, IEEE Press,2001:1-9.
[129]李惠峰,周锐.混合Petri网及其可达性分析.北京航空航天大学学报,2000,26(2):149-152.
[130]邵明珩,章昆,邬秋香. A—SMGCS系统中的助航灯光控制技术浅析.现代电子工程,2009,(3):47-49.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |