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Model-based Approach for Building Trust in Autonomous Drones through Digital Twins

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F22%3A00126492" target="_blank" >RIV/00216224:14330/22:00126492 - isvavai.cz</a>

  • Result on the web

    <a href="https://ieeexplore.ieee.org/document/9945227" target="_blank" >https://ieeexplore.ieee.org/document/9945227</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/SMC53654.2022.9945227" target="_blank" >10.1109/SMC53654.2022.9945227</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Model-based Approach for Building Trust in Autonomous Drones through Digital Twins

  • Original language description

    The 21st century is the age of automation. The automotive industry is converging towards deployment of com- plete automation by 2030. But are humans ready for it, or will they be hesitant to adopt it due to the lack of trust? To safeguard future autonomous mobility, robust run-time trust assurance and assessment is necessary. One strategy that is so far under-explored is rooted in involving the intelligence inside the autonomous agents, which could be directed towards detection of trust-breaking behaviour in other agents so that problematic vehicles are reported before they can engage in harmful behaviour. To support the progress in this direction, we propose a peer-to- peer model-based run-time trust assessment method, employing the model in terms of a Digital Twin for an autonomous vehicle (drone in our case) to ensure the trusted execution of intelligent agents. In this research, we examine the role of the Digital Twin in the trust-building scenario, and propose the characteristics of the intended Digital Twin model. To illustrate the approach, we present a case study of an autonomous-drone food delivery system and use formal approaches such as Petri Nets and Finite State Machines (FSM) to evaluate the scenario and demonstrate how trust could be built among autonomous drones or other vehicles.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10200 - Computer and information sciences

Result continuities

  • Project

    <a href="/en/project/EF19_073%2F0016943" target="_blank" >EF19_073/0016943: Internal grant agency of Masaryk University</a><br>

  • Continuities

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

Others

  • Publication year

    2022

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

  • ISBN

    9781665452588

  • ISSN

    1062-922X

  • e-ISSN

  • Number of pages

    7

  • Pages from-to

    656-662

  • Publisher name

    IEEE

  • Place of publication

    USA

  • Event location

    USA

  • Event date

    Jan 1, 2022

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article