Conflict resolution for air traffic management: a study inmultiagent hybrid systems

Air traffic management (ATM) of the future allows for the possibility of free flight, in which aircraft choose their own optimal routes, altitudes, and velocities. The safe resolution of trajectory conflicts between aircraft is necessary to the success of such a distributed control system. In this paper, we present a method to synthesize provably safe conflict resolution manoeuvres. The method models the aircraft and the manoeuvre as a hybrid control system and calculates the maximal set of safe initial conditions for each aircraft so that separation is assured in the presence of uncertainties in the actions of the other aircraft. Examples of manoeuvres using both speed and heading changes are worked out in detail     

A graph theoretic approach to authorization delegation and conflict resolution in decentralised systems

The problem of resolving conflicts in delegated authorizations has not been systematically addressed by researchers. In (Ruan and Varadharajan in Proceedings of the 7th Australasian Conference on Information Security and Privacy, pp. 271–285, 2002) we proposed a graph based framework that supports authorization delegation and conflict resolution. In this paper, we have extended the model to allow grantors of delegations to express degrees of certainties about their delegations and grants of authorizations. This expression of certainty gives the subjects (e.g. users) more flexibility to control their delegations of access rights. We propose a new conflict resolution policy based on weighted lengths of authorization paths. This policy provides a greater degree of flexibility in that it enables to specify and analyse the effect of predecessor-successor relationship as well as the weights of authorizations on the conflicts. We present a detailed algorithm to evaluate authorization delegations and conflict resolutions. The correctness proof and time complexity of the algorithm are also provided. Since in a dynamic environment, the authorization state is not static, we have considered how authorization state changes occur and have developed an algorithm to analyse authorization state transformations and given correctness proofs. Finally, we discuss how to achieve a global decision policy from local authorization policies in a distributed environment. Three integration models based on the degrees of node autonomy are proposed, and different strategies of integrating the local policies into the global policies in each model are systematically discussed.     

一种模型重构冲突消解算法

冲突是研究模型重构中的一个重要问题,多数研究将该问题的重点放在冲突检测上,通过对已知冲突的分析,找出冲突消解的手工实现方式.为实现模型重构的自动过程而寻找自动消解冲突的方法是主要研究内容.根据冲突发生的条件将冲突分为3种类型:同一规则的并行使用产生的冲突、对称冲突、非对称冲突.该方法建立在手工分析这3类重构冲突消解的基础上,将重构规则预设为一个规则矩阵,对图转换系统中出现的重构规则进行扫描.扫描结果对照规则矩阵,判断冲突是同一规则还是不同规则的并行使用所产生;分别对这两种情况下的冲突所操作的对象进行分析,根据已有手工消解方法有针对性地进行消解操作.这一算法可以初步实现并行执行的3类冲突的自动消解.     

航空器轨迹预测技术研究综述

航空器轨迹预测是流量管理、冲突检测和解脱、航空器进场排序以及异常行为监测等空中交通管理技术的基础。关于航空器轨迹预测的研究产生了许多经典的方法和应用领域。对研究航迹预测问题的背景和意义进行概述,并从数据库、基础流程和预测关键技术三个方面介绍了有关航迹预测的基础知识。其中数据库包括航空器性能数据库、航空器监视数据库和气象数据库,基础流程包括准备、预测、更新和输出四个模块,预测关键技术总结并列举了状态估计模型、动力学模型和机器学习模型三类方法的典型模型。对航迹预测系统模型进行具体分析时,进一步列举三类方法的主要研究成果并归纳各类方法的特点。对航迹预测在空中交通管理中的具体应用进行分析,包括冲突检测、到达管理和流量管理等。总结并指出了目前航迹预测问题所面临的挑战和未来的发展方向。     

基于常量条件函数依赖的冲突消解算法

目前绝大部分冲突消解方法都是基于迭代计算数据源可靠度和事实可信度的机制。当数据源较少时,数据源的可靠度难于进行评估,仅凭投票来消解冲突往往会造成较大误差。针对数据源较少时的冲突消解问题,提出基于常量条件函数依赖的冲突消解算法。根据多个数据源之间的冲突,找出冲突匹配对及对应的冲突候选值集合。考虑常量条件函数依赖中具体到部分实例子集的约束关系,将常量条件函数依赖集作为先验知识,通过判断候选值是否符合常量条件函数依赖来选择正确的候选值,避免了错误数据比例较大时直接投票选择产生的误差。通过两个真实数据集上的对比实验验证了上述算法的有效性。     

Visualizing complexities: the human limits of air traffic control

Air traffic management is organized into filters in order to prevent tactical controllers from dealing with complex conflicting situations. In this article, we describe an experiment showing that a dynamic conflict display could improve human performance on complex conflict situations. Specifically, we designed a display tool that represents the conflicting portions of aircraft trajectories and the evolution of the conflict zone when the user adds a maneuver to an aircraft. The tool allows the user to dynamically check the potential conflicting zones with the computer mouse before making a maneuver decision. We tested its utility on a population of forty students: twenty air traffic controller (ATC) students at the end of their initial training and twenty engineering students with the same background but no ATC training. They had to solve conflicts involving 2–5 aircraft with a basic display and with the dynamic visualization tool. Results show that in easy situations (2 aircraft), performance is similar with both displays. However, as the complexity of the situations grows (from 3 to 5 aircraft), the dynamic visualization tool enables users to solve the conflicts more efficiently. Using the tool leads to fewer unsolved conflicts and shorter delays. No significant differences are found between the two test groups except for delays: ATC students give maneuvers that generate less delays than engineering students. These results suggest that humans are better able to manage complex situations with the help of our conflict visualization tool.     

The role of the air traffic controller in future air traffic management: an empirical study of active control versus passive monitoring

Proposals for air traffic management such as Free Flight call for a transfer of responsibility for separation between aircraft from air traffic controllers (ATCos) to pilots. Under many proposals, the role of the ATCo will change from one of active control to passive monitoring. The present study directly compared these types of control with respect to ATCo mental workload, conflict detection, and memory. Eighteen ATCos participated in an air traffic control simulation of Free Flight procedures under moderate and high traffic load. Dependent variables included accuracy and timeliness in detecting potential conflicts, accepting and handing off aircraft, mental workload (as assessed by a secondary task, heart rate variability, and subjective ratings), and memory for aircraft location. High traffic density and passive control both degraded conflict detection performance. Actual or potential applications of this research include the recommendation that designs for future air traffic management keep authority for separation of aircraft with the controller.     

Fuzzy signal detection theory: analysis of human and machine performance in air traffic control,and analytic considerations

This paper applies fuzzy SDT (signal detection theory) techniques, which combine fuzzy logic and conventional SDT, to empirical data. Two studies involving detection of aircraft conflicts in air traffic control (ATC) were analysed using both conventional and fuzzy SDT. Study 1 used data from a preliminary field evaluation of an automated conflict probe system, the User Request Evaluation Tool (URET). The second study used data from a laboratory controller-in-the-loop simulation of Free Flight conditions. Instead of assigning each potential conflict event as a signal (conflict) or non-signal, each event was defined as a signal (conflict) to some fuzzy degree between 0 and 1 by mapping distance into the range [0, 1]. Each event was also given a fuzzy membership, [0, 1], in the set 'response', based on the perceived probability of a conflict or on the colour-coded alert severity. Fuzzy SDT generally reduced the computed false alarm rate for both the human and machine conflict systems, partly because conflicts just outside the conflict criterion used in conventional SDT, were defined by fuzzy SDT as a signal worthy of some attention. The results illustrate the potential of fuzzy SDT to provide, especially in exploratory data analysis, a more complete picture of performance in aircraft conflict detection and many other applications. Alternative analytic methods also using fuzzy SDT concepts are discussed.     

Fuzzy signal detection theory: analysis of human and machine performance in air traffic control,and analytic considerations

This paper applies fuzzy SDT (signal detection theory) techniques, which combine fuzzy logic and conventional SDT, to empirical data. Two studies involving detection of aircraft conflicts in air traffic control (ATC) were analysed using both conventional and fuzzy SDT. Study 1 used data from a preliminary field evaluation of an automated conflict probe system, the User Request Evaluation Tool (URET). The second study used data from a laboratory controller-in-the-loop simulation of Free Flight conditions. Instead of assigning each potential conflict event as a signal (conflict) or non-signal, each event was defined as a signal (conflict) to some fuzzy degree between 0 and 1 by mapping distance into the range [0, 1]. Each event was also given a fuzzy membership, [0, 1], in the set ‘response’, based on the perceived probability of a conflict or on the colour-coded alert severity. Fuzzy SDT generally reduced the computed false alarm rate for both the human and machine conflict systems, partly because conflicts just outside the conflict criterion used in conventional SDT, were defined by fuzzy SDT as a signal worthy of some attention. The results illustrate the potential of fuzzy SDT to provide, especially in exploratory data analysis, a more complete picture of performance in aircraft conflict detection and many other applications. Alternative analytic methods also using fuzzy SDT concepts are discussed.     

A strategic conflict avoidance approach based on cooperative coevolutionary with the dynamic grouping strategy

Conflict avoidance plays a crucial role in guaranteeing the safety and efficiency of the air traffic management system. Recently, the strategic conflict avoidance (SCA) problem has attracted more and more attention. Taking into consideration the large-scale flight planning in a global view, SCA can be formulated as a large-scale combinatorial optimisation problem with complex constraints and tight couplings between variables, which is difficult to solve. In this paper, an SCA approach based on the cooperative coevolution algorithm combined with a new decomposition strategy is proposed to prevent the premature convergence and improve the search capability. The flights are divided into several groups using the new grouping strategy, referred to as the dynamic grouping strategy, which takes full advantage of the prior knowledge of the problem to better deal with the tight couplings among flights through maximising the chance of putting flights with conflicts in the same group, compared with existing grouping strategies. Then, a tuned genetic algorithm (GA) is applied to different groups simultaneously to resolve conflicts. Finally, the high-quality solutions are obtained through cooperation between different groups based on cooperative coevolution. Simulation results using real flight data from the China air route network and daily flight plans demonstrate that the proposed algorithm can reduce the number of conflicts and the average delay effectively, outperforming existing approaches including GAs, the memetic algorithm, and the cooperative coevolution algorithms with different well-known grouping strategies.     

Tree-Based Concurrency Control in Distributed Groupware

We present a novel algorithm, called dARB, forsolving the concurrency control problem indistributed collaborative applications. Themain issue of concurrency control is resolvingthe conflicts resulting from simultaneousactions of multiple users. The algorithmreduces the need for manual conflict resolutionby using a distributed arbitration scheme. Themain advantages of our approach are thesimplicity of use and good responsiveness, asthere are no lock mechanisms. Our algorithmrequires the applications to use a tree as theinternal data structure. This makes itapplication independent and suitable forgeneral collaborative applications. The treerequirement is reasonable since many newapplications use XML (extensible MarkupLanguage) for data representation and exchange,and parsing XML documents results in treestructures. Example applications of thealgorithm, a group text editor and acollaborative 3D virtual environment calledcWorld, are implemented and evaluated in theDISCIPLE collaboration framework. We alsointroduce awareness widgets that users avoidgenerating the conflicting events and help inmanual conflict resolution.     

Detection and resolution of conflicting change operations in version management of process models

Version management of process models requires that different versions of process models are integrated by applying change operations. Conflict detection between individually applied change operations and conflict resolution support are integral parts of version management. For conflict detection it is utterly important to compute a precise set of conflicts, since the minimization of the number of detected conflicts also reduces the overhead for merging different process model versions. As not every syntactic conflict leads to a conflict when taking into account model semantics, a computation of conflicts solely on the syntax leads to an unnecessary high number of conflicts. Moreover, even the set of precisely computed conflicts can be extensive and their resolution means a significant workload for a user. As a consequence, adequate support is required that guides a user through the resolution process and suggests possible resolution strategies for individual conflicts. In this paper, we introduce the notion of syntactic and semantic conflicts for change operations of process models. We provide a method how to efficiently compute conflicts precisely, using a term formalization of process models and consider the subsequent resolution of the detected conflicts based on different strategies. Using this approach, we can significantly reduce the number of overall conflicts and reduce the amount of work for the user when resolving conflicts.     

An adaptive large neighborhood search heuristic for solving a robust gate assignment problem

With the rapid growth of air traffic demand, airport capacity becomes a major bottleneck within the air traffic control systems. Minor disturbances may have a large impact on the airport surface operations due to the overly tight schedules, which results in frequent gate conflict occurrences during airport’s daily operations. A robust gate schedule that is resilient to disturbances is essential for an airport to maintain a good performance. Unfortunately, there is no efficient expert system available for the airport managers to simultaneously consider the traditional cost (the aircraft tow cost, transfer passenger cost) and the robustness. To fill this gap, in this paper, we extend the traditional gate assignment problem and consider a wider scope, in which the traditional costs and the robustness are simultaneously considered. A mathematical model is first built, which leads to a complex non-linear model. To efficiently solve this model, an adaptive large neighborhood search (ALNS) algorithm is then designed. We novelly propose multiple local search operators by exploring the characteristics of the gate assignment problem. The comparison with the benchmark algorithm shows the competitiveness of proposed algorithm in solving the considered problem. Moreover, the proposed methodology also has great potential from the practical perspective since it can be easily integrated into current expert systems to help airport managers make satisfactory decisions.     

An analysis of relational complexity in an air traffic control conflict detection task

Theoretical analyses of air traffic complexity were carried out using the Method for the Analysis of Relational Complexity. Twenty-two air traffic controllers examined static air traffic displays and were required to detect and resolve conflicts. Objective measures of performance included conflict detection time and accuracy. Subjective perceptions of mental workload were assessed by a complexity-sorting task and subjective ratings of the difficulty of different aspects of the task. A metric quantifying the complexity of pair-wise relations among aircraft was able to account for a substantial portion of the variance in the perceived complexity and difficulty of conflict detection problems, as well as reaction time. Other variables that influenced performance included the mean minimum separation between aircraft pairs and the amount of time that aircraft spent in conflict.     

An analysis of relational complexity in an air traffic control conflict detection task

Theoretical analyses of air traffic complexity were carried out using the Method for the Analysis of Relational Complexity. Twenty-two air traffic controllers examined static air traffic displays and were required to detect and resolve conflicts. Objective measures of performance included conflict detection time and accuracy. Subjective perceptions of mental workload were assessed by a complexity-sorting task and subjective ratings of the difficulty of different aspects of the task. A metric quantifying the complexity of pair-wise relations among aircraft was able to account for a substantial portion of the variance in the perceived complexity and difficulty of conflict detection problems, as well as reaction time. Other variables that influenced performance included the mean minimum separation between aircraft pairs and the amount of time that aircraft spent in conflict.     

基于STN的时间冲突检测与消解

针对已有的STN一致性检验算法只能检测时间冲突而不能消解冲突的问题,以负环检测算法为基础,提出一种结合冲突检测和冲突消解的迭代算法。设计基于调整代价的冲突消解方法,对负环检测进行增量处理,可提高冲突消解的合理性和速度,减轻计划者处理冲突的负担。实验结果证明该算法具有较高的效率。     

Cooperating air traffic control agents

The key aim of cooperating air traffic control agents (CAT CA) was to comparatively analyze and evaluate the success of a multiagent system (MAS) and a single agent system (SAS) at addressing a given set of goals in a problem domain amenable to the utilization of either a MAS or SAS. The problem domain selected was air traffic control (AT C). The success of the MAS and SAS was evaluated in accordance with a set of objective criteria. The results attained support a hypothesis that the MAS is successful at addressing the given set of goals for simulation scenarios utilizing a large number of aircraft, and the SAS is successful at addressing the sameset of goals in simulation scenarios utilizing a small number of aircraft. The term success is defined as the number of cases within a given simulation scenario, where an agent detects and resolves potential air traffic conflicts, and directs aircraft adhering to expected aircraft flight times. The results attained are applicable in problem domains other than AT C, such as intelligent hospital scheduling (Decker, 1996), and road traffic congestion and traffic jam simulation (Cremer, et al., 1994).     

Human factors assessment of conflict resolution aid reliability and time pressure in future air traffic control

Though it has been reported that air traffic controllers' (ATCos') performance improves with the aid of a conflict resolution aid (CRA), the effects of imperfect automation on CRA are so far unknown. The main objective of this study was to examine the effects of imperfect automation on conflict resolution. Twelve students with ATC knowledge were instructed to complete ATC tasks in four CRA conditions including reliable, unreliable and high time pressure, unreliable and low time pressure, and manual conditions. Participants were able to resolve the designated conflicts more accurately and faster in the reliable versus unreliable CRA conditions. When comparing the unreliable CRA and manual conditions, unreliable CRA led to better conflict resolution performance and higher situation awareness. Surprisingly, high time pressure triggered better conflict resolution performance as compared to the low time pressure condition. The findings from the present study highlight the importance of CRA in future ATC operations.

Practitioner Summary: Conflict resolution aid (CRA) is a proposed automation decision aid in air traffic control (ATC). It was found in the present study that CRA was able to promote air traffic controllers' performance even when it was not perfectly reliable. These findings highlight the importance of CRA in future ATC operations.