An early design method to quantify vision obstruction: Formula One (F1) halo case study

This paper introduces a proactive ergonomics methodology to quantify vision obstruction by integrating computer-aided design (CAD), digital human modeling (DHM), and image processing. The ``rough and rapid'' approach presented in this study uses an image analysis macro to measure forward field of view (FoV) obstruction based on the snapshots collected from DHM software. The proof-of-concept design study presented in this research investigates the quantification of the obstruction caused by halo-type cockpit safety and protection equipment introduced into Formula 1 (F1) race cars in 2018. Halo is a curved bar that surrounds the driver's head over the cockpit opening and offers additional protection to drivers. However, the halo's introduction has raised obstruction-related concerns due to its vertical and horizontal bars (pillar-like elements) sitting in front of the cockpit. In this case study, a low-fidelity digital F1 race car model, including halo safety equipment, was constructed along with the manikins representing generic F1 drivers with different anthropometric characteristics. A low-fidelity DHM simulation setup, consisting of the F1 vehicle and simplified race track model, was used to collect forward FoV vision snapshots of drivers. The snapshots were then sent to an image processing software to quantify the area obscured by the halo. Overall, the results show how the methodology can supply designers with quantitative data to gain more insight into visibility concerns regarding obstruction caused by body frame and cockpit components early in preliminary design. This approach discussed in this study is particularly noteworthy during the preliminary design, where designers demand robust concept evaluation tools to evaluate concepts variants before building time-consuming and costly physical mockups.