Seeing with Touch: The Effect of Full-Body Positional Haptic Feedback During Low-Visibility Aviation Ground Operations

Objective: Through interaction between the Teslasuit and XPlane 11, we evaluate the impact of full-body positional haptic feedback during low-visibility aviation ground operations. This paper presents a working pipeline for Teslasuit-based flight simulator experiments and provides a preliminary human-in-the-loop evaluation of the system based on objective and subjective pilot performance and workload results. Method: We interface between a Teslasuit and XPlane 11 via the Unity Game engine and an application specific dynamic linked library (DLL). Source files for the interface are provided as supplementary material within a GitHub repository. The preliminary study involved six non-pilot participants completing 8 simulated taxiing tasks in a light-aircraft between two locations at Munich airport (EDDM) in low-visibility conditions. Evaluation of the haptic human machine interface (HMI) on participant performance was based on stopping distance from a threat. Subjective workload data was collected via NASA TLX questionnaires that were administered after each trial. Results: Raw TLX results were significantly lower during trials with the haptic HMI (M: 7.36, SD: 2.33) compared to trials without (M: 9.53, SD: 3.87) − (t (5) = −2.01; p = .05). Conversely, participants stopping distance (metres) from threats was larger with the haptic HMI (M: 140.44, SD: 84.84) than without (M: 119.31, SD: 33.26). Conclusions: Full-body haptic feedback warnings reduced mental workload when performing ground-based taxi operations but did not improve stopping distance. A larger sample size, with a representative pilot population, would be helpful for ascertaining a fuller understanding of full-body haptic feedback benefits within airport ground operations.