适用于多航路的概率型中期冲突探测方法

通过分析飞机飞行过程中的航迹误差,提出了估计飞行冲突可能性大小的概率型中期冲突探测的思想。针对我国民航航路由多个航路段组成的特点,提出了改进的中期冲突探测算法。该方法参考飞行过程中的最小间距点,找出两飞机在整个预测时间内的5个极小间距点作为航迹误差的累积过程,从而更精确地描述了两机相遇几何中的联合航迹误差。最后实例仿真计算表明,该算法完全能满足空中交通管制对算法实时性的要求,可以应用于实际的空中交通管制系统中。     

中期冲突探测算法的研究与设计

综合考虑飞机实际飞行中存在多个航路转弯点及空中交通管制辅助系统需满足实时准确性的要求,设计了一种改进型的中期冲突探测算法.以雷达获取的飞机的当前位置和速度矢量作为初始状态,再结合航路飞行意图信息和转弯后的航迹误差积累方法,计算整合后的各航路分段冲突发生的概率来预测冲突发生的可能性.仿真实验结果表明,该算法能有效地用于中期冲突探测.     

一种高效的中期冲突探测随机化算法

中期冲突探测是空中交通管制系统的重要功能,对飞机间未来冲突概率进行估计的随机化方法,是实现中期冲突探测的重要方法。为了解决传统的随机化方法需要进行大量运算所导致的效率低下、准确性不高等问题,通过对传统方法的改进,提出了一种高效的随机化算法。仿真实验表明,该算法极大地提高了运行效率,同时提高了计算的准确性。可以应用于实际的空管系统中。     

空中交通管制自动化系统中飞行冲突概率解析算法的应用

由于空中交通管制指挥监测系统（ATCCMS）中航迹预估的不确定性,以它为基础的冲突探测就必须采用基于概率的算法,文中介绍了一个实用的求解冲突概率的解析算法,并用蒙特卡洛方法对它进行了验证,然后对飞行冲突概率的特性做了分析研究,描述了冲突概率应用于冲突报警和冲突求解的基本思想。     

飞行计划冲突预探测算法研究

对飞行计划冲突预探测进行了彻底的研究,给出了相应的预探测算法。在对各种冲突类型进行研究的同时,针对航迹交叉时横向间隔的冲突探测——预探测中最困难的问题,给出了相关的探测模型,结合严密的数学理论推导,得出相关的求解公式,全面地解决了该问题。当冲突存在时,该算法确定地给出冲突时间段和冲突的航路段。实践表明,该算法是非常有效的。     

空中交通管制中改进型冲突探测算法研究与应用

航路区飞行中的冲突探测由于误差的存在,决定了只能采用基于概率的冲突探测算法。文章对基于布朗运动的二维冲突概率算法进行了仿真分析,得出各种因素对冲突概率的影响效果。在此基础上对算法进行了三维扩展,给出了实际应用的流程。该改进型算法已经实际应用于空中交通管制指挥监测系统(ATCCMS)中,运行结果表明改进型算法是满足有效性和实时性要求的。     

基于航路段相关的飞行冲突探测方法研究

调配航路飞行冲突是民航空管ATC区域管制的一项重要课题。文章从分析空管雷达航迹和航路之间的关系出发,提出了基于航路段分析调配航路飞行冲突的一种有效的解决方案。     

基于航路点搜索法的军用飞行器航路规划

为提高军用飞行器航路规划的效率和对威胁体的适应性,提出一种基于几何原理的、步进搜索的新航路规划方法:航路点搜索法。对禁飞区、雷达和防空武器、高山等地形障碍物进行建模,推导出航路规划时的代价函数。介绍在规划空间内如何选取航路点、使用航路点搜索法在获得的航路点中进行筛选,从而生成航路的过程和原则,并根据代价函数对规划出的航路进行寻优。通过算例对航路点搜索法进行仿真验证,结果表明,该方法简单有效,收敛性好,对威胁体的类型和数量不敏感,具有一定的工程应用价值。     

基于球形边界的ATC飞行冲突概率预测

文章根据ICAO的飞行规则对飞行器的飞行冲突进行了较详细的理论分析,将该飞行冲突过程分成两个阶段即航路巡航阶段和离场起飞、进近着陆阶段,通过简化飞行边界条件和飞行冲突状态,分别推导给出了该两个阶段需要的三维飞行冲突预测解析运算模型。该飞行冲突预测解析运算模型运算量明显得到减少,并利用Monte-Carlo仿真算法验证了该算法的精确度和可行性。     

基于约束支配多目标进化算法的航路改航方法

针对具有多目标多约束特征的航路改航问题,提出了基于约束支配的非支配排序多目标进化算法(NSGA-Ⅱ)的路径规划方法.采用了约束支配规则处理空中交通管制规则中关于改航的多个约束条件,建立个体解之间的约束支配关系.在产生初始群体时进行分区产生随机的浮点坐标,并提前筛选出符合航向角改变量约束的可接受解,增加删除算子用以处理不可接受的不可行解,进化算法迭代完成后,建立优化算子用以优化迭代产生的路径.在块状和离散状飞行限制区条件下分别进行仿真实验,实验结果表明,该方法能产生符合目标函数优化且路径复杂度较小的最优解.     

A hybrid distributed-centralized conflict resolution approach for multi-aircraft based on cooperative co-evolutionary

Conflict resolution （CR） plays a crucial role in safe air traffic management （ATM）. In this paper, we propose a new hybrid distributed-centralized tactical CR approach based on cooperative co-evolutionary named the CCDG （cooperative co-evolutionary with dynamic grouping） strategy to overcome the drawbacks of the current two types of approaches, the totally centralized approach and distributed approach. Firstly, aircraft are divided into several sub-groups based on their interdependence. Besides, a dynamic grouping strategy is proposed to group the aircraft to better deal with the tight coupling among them. The sub-groups are adjusted dynamically as new conflicts appear after each iteration. Secondly, a fast genetic algorithm （GA） is used by each sub-group to optimize the paths of the aircraft simultaneously. Thirdly, the aircraft＇s optimal paths are obtained through cooperation among different sub-groups based on cooperative co-evolutionary （CC）. An experimental study on two illustrative scenarios is conducted to compare the CCDG method with some other existing approaches and it is shown that CCDG which can get the optimal solution effectively and efficiently in near real time, outperforms most of the existing approaches including Stratway, the fast GA, a general evolutionary path planner, as well as three well-known cooperative co-evolution algorithms.     

Formal verification of conflict detection algorithms

Safety assessment of new air traffic management systems is a main issue for civil aviation authorities. Standard techniques such as testing and simulation have serious limitations in new systems that are significantly more autonomous than the older ones. In this paper, we present an innovative approach for establishing the correctness of conflict detection systems. Fundamental to our approach is the concept of trajectory, and how we represent a continuous physical trajectory by a continuous path in the x-y plane constrained by physical laws and operational requirements. From the model of trajectories, we extract, and formally prove, high-level properties that can serve as a framework to analyze conflict scenarios. We use the AILS (Airborne Information for Lateral Spacing) alerting algorithm as a case study of our approach. Published online: 19 November 2002     

Realtime multi-aircraft tracking in aerial scene with deep orientation network

Tracking the aircrafts from an aerial view is very challenging due to large appearance, perspective angle, and orientation variations. The deep-patch orientation network (DON) method was proposed for the multi-ground target tracking system, which is general and can learn the target’s orientation based on the structure information in the training samples. Such approach leverages the performance of tracking-by-detection framework into two aspects: one is to improve the detectability of the targets by using the patch-based model for the target localization in the detection component and the other is to enhance motion characteristics of the individual tracks by incorporating the orientation information as an association metric in the tracking component. Based on the DON structure, you only look once (YOLO) and faster region convolutional neural network (FrRCNN) detection frameworks with simple online and realtime tracking (SORT) tracker are utilized as a case study. The Comparative experiments demonstrate that the overall detection accuracy is improved at the same processing speed of both detection frameworks. Furthermore, the number of Identity switches (IDsw) has reduced about 67% without affecting the computational complexity of the tracking component. Consequently, the presented method is efficient for realtime ground target-tracking scenarios.     

Fast conflict detection using probability flow

Probabilistic conflict detection has recently attracted much attention from researchers due to its importance in safe automated transport systems; however, current methods struggle to accurately calculate in real-time the probability of conflict for complex vehicle maneuvers in cluttered environments. We present a formulation for the general probabilistic conflict detection problem using the flow rate of conflict probability at the boundary of a conflict zone. For Gaussian distributed vehicle states, we then derive a tight upper bound for the probability of conflict over a time period, which can be calculated in real-time using adaptive numerical integration techniques. We present two examples to illustrate the performance of this method: the first example shows that this method is very efficient for simple environments and the second example shows that this method can calculate the conflict probability upper bound in real-time even for complex vehicle maneuvers in cluttered environments.     

IPsec策略的冲突检测与协调

IPsec为信息在没有安全保护的网络中传递提供安全机制.但由于各种安全设备的安全策略描述不同,IPsec并没有被广泛采用.在分析各种异构网络和不同类型的通讯实体对通信安全要求的基础上,给出其IPsec安全策略的统一描述格式,以能够使各种安全设备、网络协调工作.在此条件下,给出设备、网络间策略冲突的简洁,高效的检测算法.最后,提出了一种策略协调算法,此算法能够提高网络的通信效率,并能够消除某些策略的冲突.     

Semantic-aided automation of interface mapping in enterprise integration with conflict detection

In enterprise integration, one of the most complex tasks is to map elements of various interfaces to each other. These interfaces often transport data in different ways. This means that some form of data transformation is needed. We present an approach where structural and semantic models of the interfaces can be used together to automate or semi-automate this otherwise tedious and error prone manual process. Some of the possible criteria for interface element mapping are shown, along with semantic conflicts and how they are detected and resolved. We also present a prototype tool, including an overview of its architecture, that enables us to test our approach and have a real-world runnable implementation that is deployable on an enterprise service bus runtime. Finally, we show how some of the steps in the mapping and conflict resolution process could be made configurable by the user, making the integration developer agnostic with respect to the technical implementation of the involved systems.     

Effects of conflict alerting system reliability and task difficulty on pilots' conflict detection with cockpit display of traffic information

A total of 24 pilots viewed dynamic encounters between their own aircraft and an intruder aircraft on a 2-D cockpit display of traffic information (CDTI) and estimated the point and time of closest approach. A three-level alerting system provided a correct categorical estimate of the projected miss distance on 83% of the trials. The remaining 17% of alerts were equally divided between misses and false alarms, of large and small magnitude. Roughly half the pilots depended on automation to improve estimation of miss distance relative to the baseline pilots, who viewed identical trials without the aid of automated alerts. Moreover, they did so more on the more difficult traffic trials resulting in improved performance on the 83% correct automation trials without causing harm on the 17% automation-error trials, compared to the baseline group. The automated alerts appeared to lead pilots to inspect the raw data more closely. While assisting the accurate prediction of miss distance, the automation led to an underestimate of the time remaining until the point of closest approach. The results point to the benefits of even imperfect automation in the strategic alerts characteristic of the CDTI, at least as long as this reliability remains high (above 80%).     

Effects of conflict alerting system reliability and task difficulty on pilots' conflict detection with cockpit display of traffic information

A total of 24 pilots viewed dynamic encounters between their own aircraft and an intruder aircraft on a 2-D cockpit display of traffic information (CDTI) and estimated the point and time of closest approach. A three-level alerting system provided a correct categorical estimate of the projected miss distance on 83% of the trials. The remaining 17% of alerts were equally divided between misses and false alarms, of large and small magnitude. Roughly half the pilots depended on automation to improve estimation of miss distance relative to the baseline pilots, who viewed identical trials without the aid of automated alerts. Moreover, they did so more on the more difficult traffic trials resulting in improved performance on the 83% correct automation trials without causing harm on the 17% automation-error trials, compared to the baseline group. The automated alerts appeared to lead pilots to inspect the raw data more closely. While assisting the accurate prediction of miss distance, the automation led to an underestimate of the time remaining until the point of closest approach. The results point to the benefits of even imperfect automation in the strategic alerts characteristic of the CDTI, at least as long as this reliability remains high (above 80%).