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The air traffic management system is under generalized upgrading process. New requirements of safety arise based on several
emerging technologies. This work presents a model to automatically verify safety of actions taken by human traffic controllers
in frequent situations. The model uses the formalism of hybrid automata, and consists basically on...
Contexts in source publication
Context 1
... with the increase of air traffic, an overload on the controller may happen and, consequently, an increase of the air traffic management risk. The use of aid tools on the conflict preview and anticipated resolution might effectively contribute to raise the operational safety level. The process of conflict detection and resolution is illustrated in Fig. 2. A first version of such a tool is drafted, that will perform the conflict preview to the following ...
Context 2
... objective is to verify if the safety conditions are held during this manoeuvre. W 2 ), i.e. the convex hull of W 1 ∪ W 2 , a set that will be important to define one of the safety conditions. It will also be seen that a safe trajectory must go through every transition window at a given sequence. ...
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Export Date: 4 October 2016
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Citations
... This is usually done on high level models like Simulink, via numerical simulations. Sometimes, formal methods are used on equivalent models like hybrid automata [10,17,18], but this has not been done on the program itself. We leave the notion of "a program correctly controlling its environment" voluntarily vague as it may cover many properties. ...
In this article, we study the interactions between a control-command program and its physical environment via sensors and
actuators. We are interested in finding invariants on the continuous trajectories of the physical values that the program
is supposed to control. The invariants we are looking for are periodic sequences of intervals that are abstractions of the
values read by the program. To compute them, we first build octrees that abstract the impact of the program on its environment.
Then, we compute a period of the abstract periodic sequence and we finally define the values of this sequence as the fixpoint
of a monotone map. We present a prototype analyzer that computes such invariants for C programs using a simple specification
language for describing the continuous environment. It shows good results on classical benchmarks for hybrid systems verification.
... We illustrate several of the themes and technologies described above with an example originally due to de Oliveira and Cugnasca. 1 The example concerns conflict detection in aircraft routing and is massively simplified, since its purpose is simply to illustrate the methods. ...
Formal methods offer the unique benefit that it is possible to examine all possible circumstances within a given scope, rather than merely sample them as with testing and simulation. This is possible even when huge numbers of discrete possibilities must be considered, such as in fault scenarios, and in the presence of real-time and continuous behavior, and when both these sources of difficulty are combined. Formal methods achieve this by using symbolic methods of analysis, and it is the computational complexity of these symbolic methods that limits and complicates their application. Recently, new methods and tools for symbolic analysis have been developed that are far more efficient and effective in practice than earlier methods. These include solvers for "satisfiability modulo theories" (SMT solvers) and methods for using these to analyze discrete and hybrid (i.e., mixed discrete and continuous) systems. In addition, new ways to apply these capabilities have been developed, such as their use for test generation, and controller synthesis, in addition to analysis. In this paper, we outline these new methods, and describe a project to extend and apply them in combination to issues in verification and testing of diagnostic and monitoring systems.
... The use of hybrid automata to model and analyze spatial networks is a relatively new subject area, and includes application to Delta-Notch signaling networks [9], coordinated control of autonomous underwater vehicles [19], and aircraft trajectories and landing protocols [7,21]. In contrast, our focus is on emergent behavior (in the form of spiral waves) in networks of cardiac myocytes, and the use of spatial superposition as an abstraction mechanism. ...
We explore the application of graph database technology to spatio-temporal model checking of cooperating cyber-physical systems-of- systems such as vehicle platoons. We present a translation of spatio-temporal automata (STA) and the spatio-temporal logic STAL to semantically equivalent property graphs and graph queries respectively. We prove a sound reduction of the spatio-temporal verification problem to graph database query solving. The practicability and efficiency of this approach is evaluated by introducing NeoMC, a prototype implementation of our explicit model checking approach based on Neo4j. To evaluate NeoMC we consider case studies of verifying vehicle platooning models. Our evaluation demonstrates the effectiveness of our approach in terms of execution time and counterexample detection.
We address the problem of specifying and detecting emergent behavior in networks of cardiac myocytes, spiral electric waves in particular, a precursor to atrial and ventricular fibrillation. To solve this problem we: (1) apply discrete mode abstraction to the cycle-linear hybrid automata (CLHA) we have recently developed for modeling the behavior of myocyte networks; (2) introduce the new concept of spatial superposition of CLHA modes; (3) develop a new spatial logic, based on spatial superposition, for specifying emergent behavior; (4) devise a new method for learning the formulae of this logic from the spatial patterns under investigation; and (5) apply bounded model checking to detect the onset of spiral waves. We have implemented our methodology as the EMERALD tool suite, a component of our EHA framework for specification, simulation, analysis, and control of excitable hybrid automata. We illustrate the effectiveness of our approach by applying EMERALD to the scalar electrical fields produced by our CELLEXCITE simulation environment for excitable-cell networks.
We show how to automatically learn the class of Hybrid Automata called Cycle-Linear Hybrid Automata (CLHA) in order to model
the behavior of excitable cells. Such cells, whose main purpose is to amplify and propagate an electrical signal known as
the action potential (AP), serve as the “biologic transistors” of living organisms. The learning algorithm we propose comprises
the following three phases: (1)Geometric analysis of the APs in the training set is used to identify, for each AP, the modes
and switching logic of the corresponding Linear Hybrid Automata. (2)For each mode, the modified Prony’s method is used to
learn the coefficients of the associated linear flows. (3)The modified Prony’s method is used again to learn the functions
that adjust, on a per-cycle basis, the mode dynamics and switching logic of the Linear Hybrid Automata obtained in the first
two phases. Our results show that the learned CLHA is able to successfully capture AP morphology and other important excitable-cell
properties, such as refractoriness and restitution, up to a prescribed approximation error. Our approach is fully implemented
in MATLAB and, to the best of our knowledge, provides the most accurate approximation model for ECs to date.
