SafetyLens: Visual Data Analysis of Functional Safety of Vehicles.
Journal
IEEE transactions on visualization and computer graphics
ISSN: 1941-0506
Titre abrégé: IEEE Trans Vis Comput Graph
Pays: United States
ID NLM: 9891704
Informations de publication
Date de publication:
02 2021
02 2021
Historique:
pubmed:
14
10
2020
medline:
14
10
2020
entrez:
13
10
2020
Statut:
ppublish
Résumé
Modern automobiles have evolved from just being mechanical machines to having full-fledged electronics systems that enhance vehicle dynamics and driver experience. However, these complex hardware and software systems, if not properly designed, can experience failures that can compromise the safety of the vehicle, its occupants, and the surrounding environment. For example, a system to activate the brakes to avoid a collision saves lives when it functions properly, but could lead to tragic outcomes if the brakes were applied in a way that's inconsistent with the design. Broadly speaking, the analysis performed to minimize such risks falls into a systems engineering domain called Functional Safety. In this paper, we present SafetyLens, a visual data analysis tool to assist engineers and analysts in analyzing automotive Functional Safety datasets. SafetyLens combines techniques including network exploration and visual comparison to help analysts perform domain-specific tasks. This paper presents the design study with domain experts that resulted in the design guidelines, the tool, and user feedback.
Identifiants
pubmed: 33048708
doi: 10.1109/TVCG.2020.3030382
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM