此篇論文中提出了一個新的環境監管規則衝突偵測方法，其運用於偵測智慧環境中使用者所制定的各種服務（在此稱為「規則」）。不同於傳統的偵測方法，此篇論文考量時間的因素，使具有時間感知的規則也能夠進行偵測。當考慮到時間的關係，這可能會使得原本衝突的規則變成有機會發生衝突或是不發生衝突，而且這也將會影響到整個系統的運作。我們基於特徵交互作用將衝突類型分成矛盾以及循環兩種，並且將時間因素也考慮到衝突類型當中，再針對這兩種衝突分別進行偵測。在矛盾這類型的衝突中，此篇論文利用時間邏輯的歸結原理來找出矛盾的規則；在循環這類型的衝突中，此篇論文將規則轉換成圖，然後再利用深度優先搜索找出圖中的返回邊，若是有返回邊存在也就能說明圖中存在著循環。此方法主要有兩個優點，第一個是在不考慮時間因素的傳統規則中，能夠有效的偵測出衝突。第二個是考慮時間因素的時間感知規則中，也能夠有效的偵測出衝突。在我們的實驗中，除了在模擬的規則資料庫中進行偵測外，我們也針對在實際的農業養殖場域中所使用的規則資料庫進行偵測。我們所提出的方法成功的偵測出智慧環境中使用者所制定的服務。 / A novel temporal-aware conflict detection method for environmental regulation which is used to detect the various services (referred to as “rules”) prescribed by users in a smart environment is proposed in this thesis. This method is different from the traditional detection methods. This thesis considers the temporal-aware so that temporal rules can be detected. When we take the temporal relationship into account, it is possible that the conflicting rules are turned into opportunistic conflicting rules or non-conflicting rules, and it also affects the operation of the entire system. We divide the conflict type into contradiction and cycle based on the feature interaction and take the temporal relationship into account, and then detect these two kinds of conflict types. In the conflict type of contradiction, this thesis uses the temporal resolution to detection conflicting rules. In the conflict type of cycle, this thesis transforms the rules into graphs, and then detect the cycles through the depth-first search (DFS) to find back edges. This method has two main advantages, the first one is that the conflict can be detected among the traditional rules which do not consider the temporal. The second is that the conflict can be effectively detected among the temporal rules. In our experiments, in addition to detecting in simulated rule databases, we also detect the rule databases used in the real greenhouse. The method we proposed successfully detect the services prescribed by the users in the intelligent environment.

No description available.

The problem of aircraft conflict detection and resolution (CDR) in uncertainty is addressed in this thesis. The main goal in CDR is to provide safety for the aircraft while minimizing their fuel consumption and flight delays. In reality, a high degree of uncertainty can exist in certain aircraft-aircraft encounters especially in cases where aircraft do not have the capabilities to communicate with each other. Through the use of a probabilistic approach and a multiple model (MM) trajectory information processing framework, this uncertainty can be effectively handled. For conflict detection, a randomized Monte Carlo (MC) algorithm is used to accurately detect conflicts, and, if a conflict is detected, a conflict resolution algorithm is run that utilizes a sequential list Viterbi algorithm. This thesis presents the MM CDR method and a comprehensive MC simulation and performance evaluation study that demonstrates its capabilities and efficiency.

Revision control mechanisms are a crucial part of information systems to keep track of changes. It is one of the key requirements for industrial application of technologies like Linked Data which provides the possibility to integrate data from different systems and domains in a semantic information space. A corresponding semantic revision control system must have the same functionality as established systems (e.g. Git or Subversion). There is also a need for branching to enable parallel work on the same data or concurrent access to it. This directly introduces the requirement of supporting merges. This paper presents an approach which makes it possible to merge branches and to detect inconsistencies before creating the merged revision. We use a structural analysis of triple differences as the smallest comparison unit between the branches. The differences that are detected can be accumulated to high level changes, which is an essential step towards semantic merging. We implemented our approach as a prototypical extension of therevision control system R43ples to show proof of concept.

Revision control mechanisms are a crucial part of information systems to keep track of changes. It is one of the key requirements for industrial application of technologies like Linked Data which provides the possibility to integrate data from different systems and domains in a semantic information space. A corresponding semantic revision control system must have the same functionality as established systems (e.g. Git or Subversion). There is also a need for branching to enable parallel work on the same data or concurrent access to it. This directly introduces the requirement of supporting merges. This paper presents an approach which makes it possible to merge branches and to detect inconsistencies before creating the merged revision. We use a structural analysis of triple differences as the smallest comparison unit between the branches. The differences that are detected can be accumulated to high level changes, which is an essential step towards semantic merging. We implemented our approach as a prototypical extension of therevision control system R43ples to show proof of concept.

The increasing demand to integrate unmanned aircraft systems (UAS) into the national airspace is motivated by the rapid growth of the UAS industry, especially small UAS weighing less than 55 pounds. Their use however has been limited by the Federal Aviation Administration regulations due to collision risk they pose, safety and regulatory concerns. Therefore, before civil aviation authorities can approve routine UAS flight operations, UAS must be equipped with sense-and-avoid technology comparable to the see-and-avoid requirements for manned aircraft. The sense-and-avoid problem includes several important aspects including regulatory and system-level requirements, design specifications and performance standards, intruder detecting and tracking, collision risk assessment, and finally path planning and collision avoidance. In this dissertation, our primary focus is on developing an collision detection, risk assessment and avoidance framework that is computationally affordable and suitable to run on-board small UAS. To begin with, we address the minimum sensing range for the sense-and-avoid (SAA) system. We present an approximate close form analytical solution to compute the minimum sensing range to safely avoid an imminent collision. The approach is then demonstrated using a radar sensor prototype that achieves the required minimum sensing range. In the area of collision risk assessment and collision prediction, we present two approaches to estimate the collision risk of an encounter scenario. The first is a deterministic approach similar to those been developed for Traffic Alert and Collision Avoidance (TCAS) in manned aviation. We extend the approach to account for uncertainties of state estimates by deriving an analytic expression to propagate the error variance using Taylor series approximation. To address unanticipated intruders maneuvers, we propose an innovative probabilistic approach to quantify likely intruder trajectories and estimate the probability of collision risk using the uncorrelated encounter model (UEM) developed by MIT Lincoln Laboratory. We evaluate the proposed approach using Monte Carlo simulations and compare the performance with linearly extrapolated collision detection logic. For the path planning and collision avoidance part, we present multiple reactive path planning algorithms. We first propose a collision avoidance algorithm based on a simulated chain that responds to a virtual force field produced by encountering intruders. The key feature of the proposed approach is to model the future motion of both the intruder and the ownship using a chain of waypoints that are equally spaced in time. This timing information is used to continuously re-plan paths that minimize the probability of collision. Second, we present an innovative collision avoidance logic using an ownship centered coordinate system. The technique builds a graph in the local-level frame and uses the Dijkstra's algorithm to find the least cost path. An advantage of this approach is that collision avoidance is inherently a local phenomenon and can be more naturally represented in the local coordinates than the global coordinates. Finally, we propose a two step path planner for ground-based SAA systems. In the first step, an initial suboptimal path is generated using A* search. In the second step, using the A* solution as an initial condition, a chain of unit masses connected by springs and dampers evolves in a simulated force field. The chain is described by a set of ordinary differential equations that is driven by virtual forces to find the steady-state equilibrium. The simulation results show that the proposed approach produces collision-free plans while minimizing the path length. To move towards a deployable system, we apply collision detection and avoidance techniques to a variety of simulation and sensor modalities including camera, radar and ADS-B along with suitable tracking schemes.

No description available.

En génie logiciel collaboratif, les systèmes de contrôle de version (SCV) jouent un rôle crucial dans la gestion des changements de code, la promotion de la collaboration et la garantie de l'intégrité des projets partagés. Cette importance s'étend à l'ingénierie dirigée par les modèles (IDM), où les experts du domaine conçoivent des modèles spécifiques au domaine (MSD). Dans ce contexte, la collaboration avec les SCV permet de coordonner les changements de modèles et de préserver l'intégrité des MSD. Cependant, les solutions existantes se concentrent principalement sur des approches génériques, considérant les modèles comme du texte générique. Ces SCV rapportent les différences entre les versions des modèles d'une manière abstraite et non intuitive pour les experts du domaine. Cela pose également des défis lors de la résolution des conflits et de la fusion des modèles, ce qui ajoute de la complexité au flux de travail des experts du domaine. L'objectif de cette thèse est de fournir des SCV spécifiques à un domaine donné en se concentrant sur les deux principaux composants des SCV, à savoir la différenciation et la fusion. Nous présentons DSMCompare, un outil de comparaison de modèles spécifique au domaine, intégré avec des capacités de détection, de résolution et de fusion de conflits de triplets de versions. DSMCompare fournit des représentations concises des différences et conflits à différents niveaux de granularité, tout en utilisant la syntaxe graphique des MSD originaux. Dans nos évaluations, DSMCompare a démontré des améliorations notables par rapport aux solutions génériques de différenciation et de fusion, notamment une réduction de la verbosité des différences rapportée, des différences exprimée en utilisant la sémantique du domaine, une détection précise des différences sémantiques et des conflits entre différentes versions d’un modèle, une résolution correcte des conflits, une diminution des interactions manuelles requises et une amélioration globale de l'efficacité pour les experts du domaine. / In the context of collaborative software engineering, version control systems (VCS) play a crucial role in managing code changes, promoting collaboration, and ensuring the integrity of shared projects. This significance extends to model-driven engineering (MDE), where domain experts design domain-specific models (DSM). In this context, collaborating with VCS aids in coordinating model changes and preserving the integrity of DSMs. However, existing solutions primarily focus on generic approaches, considering models as generic text. VCS report the differences between model versions in an abstract and unintuitive way for domain experts. This also poses challenges when resolving conflicts and merging models, adding complexity to the workflow of domain experts. The goal of this thesis is to provide domain-specific VCS for domain experts, focusing on the two main components of VCS, namely differencing and merging. We introduce DSMCompare, a domain-specific model comparison tool integrated with three-way conflict detection, resolution, and merging capabilities. DSMCompare provides concise representations of differences and conflicts at different levels of granularity, while using the graphical syntax of the original DSMs. In our evaluations, DSMCompare demonstrated significant improvements over generic differencing and merging solutions, including a reduction in reported difference verbosity, differences expressed using the semantics of the domain, accurate detection of semantic differences and conflicts between different versions of a model, correct conflict resolution, a reduction in manual interactions needed, and an overall improvement in efficiency for domain experts.