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Digital Twins for Trust Building in Autonomous Drones through Dynamic Safety Evaluation

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F23%3A00131090" target="_blank" >RIV/00216224:14330/23:00131090 - isvavai.cz</a>

  • Výsledek na webu

    <a href="http://dx.doi.org/10.5220/0011986900003464" target="_blank" >http://dx.doi.org/10.5220/0011986900003464</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.5220/0011986900003464" target="_blank" >10.5220/0011986900003464</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Digital Twins for Trust Building in Autonomous Drones through Dynamic Safety Evaluation

  • Popis výsledku v původním jazyce

    The adoption process of innovative software-intensive technologies leverages complex trust concerns in different forms and shapes. Perceived safety plays a fundamental role in technology adoption, being especially crucial in the case of those innovative software-driven technologies characterized by a high degree of dynamism and unpredictability, like collaborating autonomous systems. These systems need to synchronize their maneuvers in order to collaboratively engage in reactions to unpredictable incoming hazardous situations. That is however only possible in the presence of mutual trust. In this paper, we propose an approach for machine-to-machine dynamic trust assessment for collaborating autonomous systems that supports trust-building based on the concept of dynamic safety assurance within the collaborative process among the software-intensive autonomous systems. In our approach, we leverage the concept of digital twins which are abstract models fed with real-time data used in the run-time dynamic exchange of information. The information exchange is performed through the execution of specialized models that embed the necessary safety properties. More particularly, we examine the possible role of the Digital Twins in machine-to-machine trust building and present their design in supporting dynamic trust assessment of autonomous drones. Ultimately, we present a proof of concept of direct and indirect trust assessment by employing the Digital Twin in a use case involving two autonomous collaborating drones.

  • Název v anglickém jazyce

    Digital Twins for Trust Building in Autonomous Drones through Dynamic Safety Evaluation

  • Popis výsledku anglicky

    The adoption process of innovative software-intensive technologies leverages complex trust concerns in different forms and shapes. Perceived safety plays a fundamental role in technology adoption, being especially crucial in the case of those innovative software-driven technologies characterized by a high degree of dynamism and unpredictability, like collaborating autonomous systems. These systems need to synchronize their maneuvers in order to collaboratively engage in reactions to unpredictable incoming hazardous situations. That is however only possible in the presence of mutual trust. In this paper, we propose an approach for machine-to-machine dynamic trust assessment for collaborating autonomous systems that supports trust-building based on the concept of dynamic safety assurance within the collaborative process among the software-intensive autonomous systems. In our approach, we leverage the concept of digital twins which are abstract models fed with real-time data used in the run-time dynamic exchange of information. The information exchange is performed through the execution of specialized models that embed the necessary safety properties. More particularly, we examine the possible role of the Digital Twins in machine-to-machine trust building and present their design in supporting dynamic trust assessment of autonomous drones. Ultimately, we present a proof of concept of direct and indirect trust assessment by employing the Digital Twin in a use case involving two autonomous collaborating drones.

Klasifikace

  • Druh

    D - Stať ve sborníku

  • CEP obor

  • OECD FORD obor

    10200 - Computer and information sciences

Návaznosti výsledku

  • Projekt

    Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

  • Návaznosti

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Ostatní

  • Rok uplatnění

    2023

  • Kód důvěrnosti údajů

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Údaje specifické pro druh výsledku

  • Název statě ve sborníku

    18th International Conference on Evaluation of Novel Approaches to Software Engineering - ENASE

  • ISBN

    9789897586477

  • ISSN

    2184-4895

  • e-ISSN

  • Počet stran výsledku

    11

  • Strana od-do

    629-639

  • Název nakladatele

    SciTePress

  • Místo vydání

    Neuveden

  • Místo konání akce

    Neuveden

  • Datum konání akce

    1. 1. 2023

  • Typ akce podle státní příslušnosti

    WRD - Celosvětová akce

  • Kód UT WoS článku

    001119034200064