论文标题
Safetylens：车辆功能安全性的视觉数据分析
SafetyLens: Visual Data Analysis of Functional Safety of Vehicles
论文作者
论文摘要
现代汽车从仅仅是机械机器到拥有完整的电子系统来发展，从而增强了车辆动态和驾驶员体验。但是，这些复杂的硬件和软件系统（如果设计不正确）可能会遇到可能损害车辆，乘员和周围环境的安全性的故障。例如，激活制动器以避免碰撞的系统在正常运行时会挽救生命，但如果以与设计不一致的方式施加刹车，可能会导致悲剧性的结果。从广义上讲，进行的分析是为了最大程度地降低此类风险落入一个称为功能安全的系统工程领域。在本文中，我们提出了Safetylens，这是一种视觉数据分析工具，可帮助工程师和分析师分析汽车功能安全数据集。 Safetylens结合了包括网络探索和视觉比较的技术，以帮助分析师执行特定领域的任务。本文向设计指南，工具和用户反馈的域专家提供了设计研究。
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.
