1.题目和关键词
Title: Coloured Petri Net-based Traffic Collision Avoidance System encounter model for the analysis of potential induced collisions
用于分析潜在诱发碰撞的基于有色Petri网的空中防撞系统遭遇模型
TCAS（The Traffic Alert and Collision Avoidance System）交通警报和防撞系统；
Encounter model遭遇模型；
State space状态空间；
Potential collision scenario潜在碰撞场景；
Petri net Petri网.
2.摘要
The Traffic Alert and Collision Avoidance System (TCAS) is a world-wide accepted last-resort means of reducing the probability and frequency of mid-air collisions between aircraft. Unfortunately, it is widely known that in congested airspace, the use of the TCAS may actually lead to induced collisions. Therefore, further research regarding TCAS logic is required. In this paper, an encounter model is formalised to identify all of the potential collision scenarios that can be induced by a resolution advisory that was generated previously by the TCAS without considering the downstream consequences in the surrounding traffic. The existing encounter models focus on checking and validating the potential collisions between trajectories of a specific scenario. In contrast, the innovative approach described in this paper concentrates on quantitative analysis of the different induced collision scenarios that could be reached for a given initial trajectory and a rough specification of the surrounding traffic. This approach provides valuable information at the operational level. Furthermore, the proposed encounter model can be used as a test-bed to evaluate future TCAS logic changes to mitigate potential induced collisions in hot spot volumes. In addition, the encounter model is described by means of the coloured Petri net (CPN) formalism. The resulting state space provides a deep understanding of the cause-and-effect relationship that each TCAS action proposed to avoid an actual collision with a potential new collision in the surrounding traffic. Quantitative simulation results are conducted to validate the proposed encounter model, and the resulting collision scenarios are summarised as valuable information for future air traffic management (ATM) systems.
交通警报和防撞系统（TCAS）是一种世界范围内公认的降低飞机之间空中碰撞概率和频率的最终手段。不幸的是，众所周知，在拥挤的空域中，使用TCAS实际上可能导致诱导碰撞。因此，需要对TCAS逻辑进行进一步的研究。在本文中，遭遇模型被正式化，以识别所有可能发生碰撞的场景，这些场景可能是由TCAS生成的未考虑周围交通下游后果的解决方案引起的。现有的遭遇模型专注于检查和验证特定场景的轨迹之间的潜在碰撞。相比之下，本文描述的创新方法集中于对给定的初始轨迹和周围交通的粗略规程可能产生的不同诱发碰撞场景的定量分析。这种方法在操作层面提供了有价值的信息。此外，所提出的遭遇模型可以用作评估未来TCAS逻辑变化的测试平台，以减轻热点区域中潜在的诱导碰撞。此外，采用有色Petri网（CPN）描述了遭遇模型。结果状态空间提供了对因果关系的深刻理解，每个TCAS动作都建议采用这种因果关系来避免实际碰撞与周围交通中潜在的新碰撞。定量仿真结果验证了所提出的遭遇模型，并将碰撞场景总结为未来空中交通管理（ATM）系统中有价值的信息。
3.创新点、学术价值
A mathematical model for the TCAS II algorithm was developed to be potentially used in a TCAS-TCAS encounter. TCAS II provides TAs to warn pilots of the encounter with neighbouring traffic and RAs to prevent a collision by offering a suggested resolution manoeuvre to pilots to execute an avoidance manoeuvre in the vertical direction. Using a series of mathematical equations, this CA process has been conceptually described. The process has also been used as the theoretical basis for construction of the encounter model.
（1）开发了TCAS II算法的数学模型，可在TCAS-TCAS遭遇中使用。TCAS II提供交通咨询（TAs）来警告飞行员与邻近交通的相遇，向飞行员提供决议咨询（RAs）执行垂直方向上的回避策略来避免碰撞。利用一系列数学方程，对CA（collision avoidance）过程进行了概念性描述。该过程也被用作构建遭遇模型的理论基础。
A novel scenario generation process of potential collisions was proposed. The only input of this model is the aircraft trajectory and the number of intruder aircraft, while the inputs of most other encounter models (Netjasov et al., 2013; Kochenderfer et al., 2010; Billingsley et al.,2009; Tang et al., 2014) are the initial states (e.g., trajectories) of all involved aircraft for the analysis of particular traffic geometries. In contrast, the proposed model presented in this paper aims to generate the potential collision scenarios for a certain number of aircraft, based on the trajectory of just one instance representative aircraft, rather than to test whether a multi-aircraft scenario contains a potential collision or not. The generated encounter scenarios may not be credible within the normal operation of the ATC system, as some of them are designed through the use of different cruising flight levels.
（2）提出了一种新的潜在碰撞场景生成过程。该模型的唯一输入是飞机的轨迹和入侵飞机的数量，而其他大多数遭遇模型的输入是所有相关飞机的初始状态（例如，轨迹），用于分析特定的交通几何形状。相比之下，本文提出的模型旨在根据一架典型飞机的飞行轨迹，生成一定数量的潜在碰撞场景，而不是测试一个多飞机的场景是否包含潜在的碰撞。在ATC系统的正常运行中，所生成的遭遇情景可能并不可信，因为其中一些情景是通过使用不同的巡航飞行高度而设计的。
The encounter model is represented in the CPN formalism. This causal model depicts the procedure that takes an aircraft with a known initial state into various induced collision scenarios containing multiple TCAS-equipped aircraft. With the state space, the model provides a better understanding of the potential collision occurrences for risk assessment by comprehending the cause-effect relationship of each action. The initial states of multiple aircraft that are involved in the scenarios can be generated one by one. Finally, all of the possible situations (state space) can be represented for subsequent analysis to summarise the typical induced collision scenarios.
（3）遭遇模型用CPN形式表示。该因果模型描述了将具有已知初始状态的飞机带入包含多个装有TCAS的飞机的各种诱发的碰撞场景的过程。在状态空间中，该模型通过理解每个动作的因果关系，可以更好地理解潜在的碰撞事件，以进行风险评估。可以逐个生成参与场景的多架飞机的初始状态。最后，所有可能的情况（状态空间）都可以表示出来，以便进行后续分析，总结出典型的诱导碰撞场景。
A summary is provided of the typical induced collision scenarios based on the simulation results of the causal model. Quantitative measurement experiments were conducted to validate the feasibility and effectiveness of the encounter model. In addition, for scenarios involving three or four aircraft (representative of almost all of the factual situations), the detailed process of a collision and the typical scenarios were illustrated and described in detail.
（4）根据因果模型的仿真结果，总结了典型的诱导碰撞场景。进行定量测量实验以验证遭遇模型的可行性和有效性。此外，对于涉及三架或四架飞机的情况（代表几乎所有的实际情况），详细说明和描述了碰撞的详细过程和典型情况。
4.对结论的理解和对学习工作的启发
TCAS旨在直接向飞行员提供最终的避撞指南，长期的实践经验证明了TCAS的实用性和效率。然而， 即使在所有涉及的飞机都装有TCAS的情况下，也可能在特殊情况下发生碰撞。当涉及多架飞机时，TCAS实际上会引发一场原本不会发生的碰撞，尤其是在周围交通密集的情况下。公共领域缺乏因果模型来描述可能引发诱导碰撞的周围交通场景；此类场景可用于比较实际交通场景，以降低碰撞频率。开发这个因果模型的动机是为了识别TCAS诱发的碰撞，并支持对当前和先进的ATM概念（包括TCAS）进行安全分析的后续研究。
未来研究计划：
（1）开发模式识别工具以识别可能存在潜在诱发碰撞的交通场景；
（2）利用所提出的因果模型来促进当前TCAS逻辑的改进，其目的是通过增强CA性能来解决未来繁忙和拥挤的交通问题。