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

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10200 - Computer and information sciences

Projekt

<a href="/cs/project/EF19_073%2F0016943" target="_blank" >EF19_073/0016943: Interní grantová agentura Masarykovy univerzity</a><br>

Návaznosti

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

Rok uplatnění

2022

Kód důvěrnosti údajů

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

Název statě ve sborníku

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

ISBN

9781665452588

ISSN

1062-922X

e-ISSN

—

Počet stran výsledku

7

Strana od-do

656-662

Název nakladatele

IEEE

Místo vydání

USA

Místo konání akce

USA

Datum konání akce

1. 1. 2022

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—