Graphical composite modeling and simulation for multi-aircraft collision avoidance
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Graphical composite modeling and simulation for multi-aircraft collision avoidance Feng Zhu1
· Jun Tang1
Received: 4 June 2019 / Revised: 6 September 2020 / Accepted: 11 September 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Modeling and simulation for multi-aircraft collision avoidance to understand the mechanistic behavior is an important activity. Building models using general programming language typically requires specialist knowledge, and this limits the spread of modeling and simulation approach among multi-aircraft collision avoidance scenario. Thus, a software environment is needed to support convenient development of models by assembling components, when analysis demands changes. In this work, the graphical composite modeling and simulation software (GMAS extended) for multi-aircraft collision avoidance is introduced, with the basic graphical components and a graphical assembly editor. We define the serial and parallel execution semantics of GMASE-based model and then introduce the high-level graphical modeling interface, the low-level runtime engine of GMAS, and the simulation-based decision tree, which transforms a complex decision-making process into a collection of simpler decisions of finding the no collision or optimal sequence from some initial state to the goal state. To validate its efficiency and practicability, a three-aircraft collision avoidance model with TCAS operations is built on GMAS, which shows that using GMAS increases reusability and hiding complexity in graphical programming by splitting complex behavior into data flow and function components. The experimental result proves that GMAS not only provides a better representation for multi-aircraft collision avoidance, but also a useful approach for analyzing the potential collision occurrences. Keywords Graphical composite modeling · Multi-aircraft collision avoidance · Event-driven modeling and simulation · Simulation-based decision tree
1 Introduction Collision avoidance between aircraft is considered as a key concern in civil and military operation scenarios [1], because very severe damage or the total destruction of the aircraft involved result from the collision. Aircraft must have the ability to autonomously plan trajectories that are away from collisions with static obstacles. Meanwhile, equipment and algorithm will be also needed to ensure that the aircraft avoids Communicated by Robert Pettit. This work was supported in part by the National Natural Science Foundation of China under Grant 61903368.
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Jun Tang [email protected] Feng Zhu [email protected]
1
College of Systems Engineering, National University of Defense Technology, Changsha, China
other aircraft during the flight, such as the Traffic Alert and Collision Avoidance System (TCAS) [2], which is designed to reduce the risk of mid-air collision between aircraft and it is mandated worldwide on large aircraft. Due to the lack of real data accumulated of multi-aircraft collisions and the dynamic characteristics of
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