Situation Coverage Based Safety Analysis of an Autonomous Aerial Drone in a Mine Environment

Nawshin Mannan Proma; Victoria J. Hodge; Rob Alexander

Situation Coverage Based Safety Analysis of an Autonomous Aerial Drone in a Mine Environment

Nawshin Mannan Proma, Victoria J. Hodge, Rob Alexander

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Abstract—If we want to integrate autonomous aerial drones into safety-critical contexts, particularly in dynamic and hazardous environments like mining operations, we need to rigorously assure their safety. Despite significant technological advancements in drone technology over the past decade, this
remains a challenge. The current safety engineering methods employed in drones cannot demonstrate convincingly that AI techniques can effectively mitigate unsafe situations with a specified level of confidence and reliability. In this paper, we present a brief study of various approaches, with particular focus
on the situation coverage-based approach. A key challenge lies in identifying a finite set of representative situations for testing from the infinite possibilities that could occur in real-world scenarios. This research contributes to advancing our understanding of situation coverage based safety assessment methodologies and coverage criteria.

Original language	English
Title of host publication	The Yorkshire Innovation in Science and Engineering Conference (YISEC) 2024
Publication status	Published - 20 Jun 2024

Bibliographical note

This is an author-produced version of the published paper. Uploaded in accordance with the University’s Research Publications and Open Access policy.

Access to Document

Final Version of YISEC paper - rob.alexander@york.
This is an author-produced version of the published paper. Uploaded in accordance with the University’s Research Publications and Open Access policy.
Accepted author manuscript, 241 KBLicence: CC BY

Cite this

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title = "Situation Coverage Based Safety Analysis of an Autonomous Aerial Drone in a Mine Environment",

abstract = "Abstract—If we want to integrate autonomous aerial drones into safety-critical contexts, particularly in dynamic and hazardous environments like mining operations, we need to rigorously assure their safety. Despite significant technological advancements in drone technology over the past decade, thisremains a challenge. The current safety engineering methods employed in drones cannot demonstrate convincingly that AI techniques can effectively mitigate unsafe situations with a specified level of confidence and reliability. In this paper, we present a brief study of various approaches, with particular focuson the situation coverage-based approach. A key challenge lies in identifying a finite set of representative situations for testing from the infinite possibilities that could occur in real-world scenarios. This research contributes to advancing our understanding of situation coverage based safety assessment methodologies and coverage criteria.",

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AU - Proma, Nawshin Mannan

AU - Hodge, Victoria J.

AU - Alexander, Rob

N1 - This is an author-produced version of the published paper. Uploaded in accordance with the University’s Research Publications and Open Access policy.

PY - 2024/6/20

Y1 - 2024/6/20

N2 - Abstract—If we want to integrate autonomous aerial drones into safety-critical contexts, particularly in dynamic and hazardous environments like mining operations, we need to rigorously assure their safety. Despite significant technological advancements in drone technology over the past decade, thisremains a challenge. The current safety engineering methods employed in drones cannot demonstrate convincingly that AI techniques can effectively mitigate unsafe situations with a specified level of confidence and reliability. In this paper, we present a brief study of various approaches, with particular focuson the situation coverage-based approach. A key challenge lies in identifying a finite set of representative situations for testing from the infinite possibilities that could occur in real-world scenarios. This research contributes to advancing our understanding of situation coverage based safety assessment methodologies and coverage criteria.

AB - Abstract—If we want to integrate autonomous aerial drones into safety-critical contexts, particularly in dynamic and hazardous environments like mining operations, we need to rigorously assure their safety. Despite significant technological advancements in drone technology over the past decade, thisremains a challenge. The current safety engineering methods employed in drones cannot demonstrate convincingly that AI techniques can effectively mitigate unsafe situations with a specified level of confidence and reliability. In this paper, we present a brief study of various approaches, with particular focuson the situation coverage-based approach. A key challenge lies in identifying a finite set of representative situations for testing from the infinite possibilities that could occur in real-world scenarios. This research contributes to advancing our understanding of situation coverage based safety assessment methodologies and coverage criteria.

M3 - Conference contribution

BT - The Yorkshire Innovation in Science and Engineering Conference (YISEC) 2024

ER -