Task Simulation Automation via Digital Human Models: A Case Study on Cockpit Fire and Smoke Emergencies

Abstract

This research introduces a Digital Human Modeling (DHM) based early design framework to automate task analysis and workplace ergonomics for emergencies and provides a proof-of-concept demonstration of the automation framework within the context of cockpit fire and smoke case study. DHM brings significant advantages to explore human-centered design issues by enabling human-product or human-environment interaction analysis within a computer or virtual environment. However, a substantial problem in designing with DHM is the reliance on manual methods during simulation setup and ergonomics analysis. A majority of the DHM workflow requires user input via controllers such as a keyboard, mouse, or wand. Manually creating DHM simulation involves tedious object orientation and task manipulations, which add extra time and effort and decrease the usefulness of DHM as an early design solution. Moreover, DHM design studies within the transportation domain often focus on ergonomics evaluations of tasks that occur in ideal or nearly ideal settings. There is a lack of DHM design tools that concentrate on emergencies. The case study depicted in this paper aims to implement a proactive ergonomics approach via the automation framework to assess reach gap and percent loss in luminance issues in cockpit smoke and fire emergencies. Overall, this research demonstrates how the proposed automation framework automates existing DHM toolkits and extends the capabilities of DHM through third-party technology integration.