一类无冲突轨迹规划方案

在新一代空中交通管理自动化系统实施方案中,航迹规划模块在基于航迹的航空器运行过程中扮演着重要角色.为了在大流量、高密度和小间隔条件下获取多航空器无冲突轨迹,针对不同的航路空间分布结构,基于航路冲突点保护区竞争机制,构建了空域多航空器极大代数耦合模型和多航空器冲突预调配模型,根据管制间隔约束建立了模型输入、状态和输出之间的约束关系.采用调整航空器过冲突点时刻和初始放行时刻两种策略,提出了一种多航空器轨迹规划优化模型.算例分析表明,所提出的多航空器轨迹规划模型可行有效.     

Maximizing the number of conflict-free aircraft using mixed-integer nonlinear programming

We address the conflict detection and resolution problem in air traffic control, where an aircraft conflict is a loss of separation between aircraft trajectories. Conflict avoidance is crucial to ensure flight safety and remains a challenging traffic control problem. We focus on speed control to separate aircraft and consider two approaches: (i) maximize the number of conflicts resolved and (ii) identify the largest set of conflict-free aircraft. Both problems are modeled using mixed-integer nonlinear programming and a tailored greedy algorithm is proposed for the latter. Computational efficiency is improved through a pre-processing algorithm which attempts to reduce the size of the conflict resolution models by detecting the existence of pairwise potential conflicts. Numerical results are provided after implementing the proposed models and algorithms on benchmark conflict resolution instances. The results highlight the benefits of using the proposed pre-processing step as well as the versatility and the efficiency of the proposed models.     

Delta-oriented model-based integration testing of large-scale systems

Software architecture specifications are of growing importance for coping with the complexity of large-scale systems. They provide an abstract view on the high-level structural system entities together with their explicit dependencies and build the basis for ensuring behavioral conformance of component implementations and interactions, e.g., using model-based integration testing. The increasing inherent diversity of such large-scale variant-rich systems further complicates quality assurance. In this article, we present a combination of architecture-driven model-based testing principles and regression-inspired testing strategies for efficient, yet comprehensive variability-aware conformance testing of variant-rich systems. We propose an integrated delta-oriented architectural test modeling and testing approach for component as well as integration testing that allows the generation and reuse of test artifacts among different system variants. Furthermore, an automated derivation of retesting obligations based on accurate delta-oriented architectural change impact analysis is provided. Based on a formal conceptual framework that guarantees stable test coverage for every system variant, we present a sample implementation of our approach and an evaluation of the validity and efficiency by means of a case study from the automotive domain.     

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.     

求解机场终端区飞机着陆调度问题的遗传算法

空中管制员需为到达的飞机安排跑道并计算着陆时间,以飞机空中延误最小为出发点研究了多跑道的飞机着陆调度问题,约束条件为每架飞机的着陆时间应落在规定的时间窗内及相邻两架飞机应满足最小时间间隔。针对该问题设计了一种遗传算法对问题进行求解,其中染色体由飞机排序链表和跑道链表组成,相应的交叉和变异算子也做了改进设计。仿真实验用数据库OR-Library中的实例验证了该算法的有效性。     

Improving nearest neighbor classification using Ensembles of Evolutionary Generated Prototype Subsets

One of the most accurate types of prototype selection algorithms, preprocessing techniques that select a subset of instances from the data before applying nearest neighbor classification to it, are evolutionary approaches. These algorithms result in very high accuracy and reduction rates, but unfortunately come at a substantial computational cost. In this paper, we introduce a framework that allows to efficiently use the intermediary results of the prototype selection algorithms to further increase their accuracy performance. Instead of only using the fittest prototype subset generated by the evolutionary algorithm, we use multiple prototype subsets in an ensemble setting. Secondly, in order to classify a test instance, we only use prototype subsets that accurately classify training instances in the neighborhood of that test instance. In an experimental evaluation, we apply our new framework to four state-of-the-art prototype selection algorithms and show that, by using our framework, more accurate results are obtained after less evaluations of the prototype selection method. We also present a case study with a prototype generation algorithm, showing that our framework is easily extended to other preprocessing paradigms as well.     

Test Synthesis from UML Models of Distributed Software

The object-oriented software development process is increasingly used for the construction of complex distributed systems. In this context, behavior models have long been recognized as the basis for systematic approaches to requirements capture, specification, design, simulation, code generation, testing, and verification. Two complementary approaches for modeling behavior have proven useful in practice: interaction-based modeling (e.g., UML sequence diagrams) and state-based modeling (e.g., UML statecharts). Building on formal V&V techniques, in this article we present a method and a tool for automated synthesis of test cases from scenarios and a state-based design model of the application, remaining entirely within the UML framework. The underlying "on the fly" test synthesis algorithms are based on the input/output labeled transition system formalism, which is particularly appropriate for modeling applications involving asynchronous communication. The method is eminently compatible with classical OO development processes since it can be used to synthesize test cases from the scenarios used in early development stages to model global interactions between actors and components, instead of these test cases being derived manually. We illustrate the system test synthesis process using an air traffic control software example     

OpenFlow协议IPv6属性测试研究

鉴于SDN网络中数据转发与控制相互分离的特性,OpenFlow协议在其南向接口中扮演着重要的角色。随着下一代互联网的发展,IPv4可供分配的地址资源已然耗尽,瓶颈地位益发凸显。如何尽快部署IPv6,使其服务于社会生产与生活,使得当前网络与IPv6网络长期共存或平滑过渡到IPv6网络是工业界与学术界要解决的问题。SDN则提供了这样一个选项,其中OpenFlow协议是否支持IPv6协议便成为我们关注的重点。通过形式化方法对OpenFlow协议进行形式化建模,得到其非确定性有限状态机模型,在此基础上得到其测试生成树,以指导测试。同时,对于其是否支持IPv6进行重点关注,利用组合测试的方法,产生了167条测试例。 完成了测试引擎的开发,支持高效的测试生成算法,以及测试执行与判定。利用此测试引擎,以上述测试例为测试输入,执行测试过程,同时进一步对测试结果进行分析,得到了定量的分析结果,符合预期要求。     

Evolutionary testing of autonomous software agents

A system built in terms of autonomous software agents may require even greater correctness assurance than one that is merely reacting to the immediate control of its users. Agents make substantial decisions for themselves, so thorough testing is an important consideration. However, autonomy also makes testing harder; by their nature, autonomous agents may react in different ways to the same inputs over time, because, for instance they have changeable goals and knowledge. For this reason, we argue that testing of autonomous agents requires a procedure that caters for a wide range of test case contexts, and that can search for the most demanding of these test cases, even when they are not apparent to the agents’ developers. In this paper, we address this problem, introducing and evaluating an approach to testing autonomous agents that uses evolutionary optimisation to generate demanding test cases. We propose a methodology to derive objective (fitness) functions that drive evolutionary algorithms, and evaluate the overall approach with two simulated autonomous agents. The obtained results show that our approach is effective in finding good test cases automatically.     

一种组合测试用例生成的可配置混合算法

组合测试是一种经过实践证明的科学有效的测试方法,其研究重点之一是组合测试用例集的生成算法。基于参数顺序渐进扩充策略IPO(In-Parameter-Order)是其中一种具有代表性的通用算法,其优势在于水平扩充算法的可选择性和测试用例集的可扩展性。算法在提取影响IPO策略效果的参数的基础上,给出可配置的IPO策略;采用遗传算法(Genctic-Algorithm)配置IPO策略中的水平扩充,得到新的混合算法IPO_GA。通过实验对可配置IPO策略中各个参数对算法的影响进行了对比分析;将IPO_ GA与部分已有算法进行了比较,结果表明在水平扩充过程中染色体较短时,IPO_GA效果较好;在解空间规模过大而导致染色体较长时,IPO_GA效果略差。     

A Parallel Genetic Algorithm Based on Spark for Pairwise Test Suite Generation

Pairwise testing is an effective test generation technique that requires all pairs of parameter values to be covered by at least one test case. It has been proven that generating minimum test suite is an NP-complete problem. Genetic algorithms have been used for pairwise test suite generation by researchers. However, it is always a time-consuming process, which leads to significant limitations and obstacles for practical use of genetic algorithms towards large-scale test problems. Parallelism will be an effective way to not only enhance the computation performance but also improve the quality of the solutions. In this paper, we use Spark, a fast and general parallel computing platform, to parallelize the genetic algorithm to tackle the problem. We propose a two-phase parallelization algorithm including fitness evaluation parallelization and genetic operation parallelization. Experimental results show that our algorithm outperforms the sequential genetic algorithm and competes with other approaches in both test suite size and computational performance. As a result, our algorithm is a promising improvement of the genetic algorithm for pairwise test suite generation.     

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.     

Dynamics and control technologies in air traffic management

Dynamics and Control technologies play a central role in the development and operation of decision support systems of modern air traffic management systems. Recent emergence of Global Navigation Satellite Systems and satellite-based augmentation systems have enabled higher precision execution of aircraft trajectories, opening-up the potential for the implementing more quantitative air traffic management approaches. Already, this navigation capability is enabling higher traffic through puts, and safer operation of aircraft in the proximity of the terrain at several major airports in the US. This paper discusses the aircraft trajectory optimization, conflict resolution algorithms, and traffic flow management problems which form the essential components of the evolving air traffic management system. It will be shown that Optimal Control Theory, Model Predictive Control and the Discrete Event Systems theory form the underlying analytical machinery in this domain. Finally, the paper will outline some of the algorithms for realizing the Trajectory Based Operations concept, currently being developed for future air traffic management.     

自动化单元测试框架NUnit的改进设计与实现

软件测试对确保软件质量有着不可替代的作用。自动化测试框架有效提高了测试效率,自动化测试框架的成熟是软件测试走向标准化的必经之路。文章改进了自动化单元测试框架NUnit,使测试代码和测试数据分离,解决了使用NUnit测试时测试代码存在大量冗余的问题。在改进的NUnit框架中,相似的测试用例只需测试人员编写一次,框架将自动生成其他测试用例。     

先进飞行器大气数据传感技术的发展与展望

大气数据传感技术通过直接或间接的方式获取飞行器周围的气流特性,对保障飞行器飞行安全、提高飞行性能具有重要的意义和价值,也是各个时期先进飞行器性能提升的关键因素。针对各个时期先进飞行器性能方面的需求,各国专家和学者从系统架构、感知方法、数据处理算法等多个角度开展了对大气数据传感技术的研究,基于相关研究成果提出了多种具备不同特点的大气数据传感技术,部分技术已经在目前的各类先进飞行器上得到了广泛应用。随着未来新一代先进飞行器的性能特点逐渐明确,面向新一代先进飞行器性能需求的大气数据传感技术将朝着一体化、信息化和智能化的方向发展。     

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.     

基于智能优化算法的测试数据生成综述

软件测试是一种极为有效的软件质量保证手段。测试数据生成是软件测试的关键。基于智能优化算法的测试数据生成方法为自动化的测试数据生成提供了解决问题的一个有效手段。首先重点总结归纳了在基于智能优化算法的测试数据生成中使用最为频繁的两种算法：遗传算法和粒子群优化算法的研究成果,分析了研究现状,接着简单介绍了基于智能优化算法的测试数据生成工具：AUSTIN和EvoSuite,最后对存在的问题及未来的研究内容进行了尝试性的探讨。     

飞机相遇模型仿真工具的研究

飞机的自主控制方法是空管领域研究的重点,尤其是飞机自主控制中的碰撞避险系统。本文提出了基于贝叶斯网络的飞机相遇模型,并以此模型为基础生成随机的相遇仿真数据。在实现仿真的过程中,本文利用有限的中国民航飞机飞行数据,先仿真一架飞机的航迹,在此基础上仿真两架相遇飞机每秒的高度、速度、加速度、转角速率大小,利用飞机相遇模型来依概率产生模拟相遇数据。此仿真航迹是没有任何碰撞预警情况下的航迹,两架飞机在相距一定距离之外均不会自主做出回避。本文利用了Matlab作为开发平台。