A model-driven framework for distributed simulation of autonomous systems
Title | A model-driven framework for distributed simulation of autonomous systems |
Publication Type | Conference Paper |
Year of Publication | 2015 |
Authors | Bocciarelli, P., Andrea D'Ambrogio, A. Giglio, and E. Paglia |
Editor | |
Conference Name | Simulation Series |
Publisher | The Society for Modeling and Simulation International |
Keywords | Autonomous systems, Cost effectiveness, Distributed simulation techniques, Distributed simulations, MDA, Model driven development, Model transformation technique, Search and rescue operations, Simulation-based analysis, Software architecture |
Abstract | The adoption of systems with autonomous capabilities is becoming more and more relevant in many real-world operational scenarios, in which risky operations have to be carried out (e.g., a military battlefield or a search-and-rescue operation). In this context, innovative approaches should be introduced at design time to ensure that the system will achieve the mission objectives at operation time. To this purpose, distributed simulation techniques have shown to be effective to deal with the inherent complexity of the environment to be simulated, which generally includes several interacting entities. Unfortunately, currently available distributed simulation standards, such as HLA (High Level Architecture), require a non-negligible effort and significant skills in terms of both simulation methodologies and related implementation technologies. In this respect, this paper focuses on the simulationbased analysis of systems with autonomous capabilities and introduces a model-driven approach to support the automated generation of HLA-based distributed simulations. The proposed approach is founded on the use of model transformation techniques and allows system designers to carry out a timely and cost-effective simulation-based analysis of the operational system without being required to own specific distributed simulation skills. © 2015 Society for Modeling & Simulation International (SCS). |
URL | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84928155948&partnerID=40&md5=9e8205a446169e040469dff647e9cfa3 |