SafetyLens: Visual Data Analysis of Functional Safety of Vehicles

Arpit Narechania, Ahsan Qamar, Alex Endert

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View presentation:2020-10-29T19:15:00ZGMT-0600Change your timezone on the schedule page
2020-10-29T19:15:00Z
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SafetyLens is a visual analysis tool that assists domain experts perform Functional Safety analysis on automobile systems by modeling the domain-specific data as a network and presenting it in an interactive visualization system. It supports exploratory analysis of a single dataset (network exploration, direct manipulation) as well as comparative analysis among multiple datasets (network comparison, set visualization). Functional Safety analysis is a systems engineering technique performed to minimize unreasonable risks associated with the electrical and electronic systems in vehicles.
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Keywords

Visual data analysis, Design study, Network visualization, Functional safety, Automotive engineering

Abstract

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.