The effect of heads-up-display (HUD) goggles on skiing and snowboarding speeds

Date created: 
2016-06-27
Identifier: 
etd9647
Keywords: 
Snowsports
Wearable Technology
Music
Safety
Risk
Alpine Resort Management
Abstract: 

This study empirically explores whether the use of heads-up-display (HUD) goggles increases the risk in ski areas by increasing skiing and snowboarding speeds. Twenty- seven skiers and snowboarders participated in a repeated measures experiment that included a control session without the HUD goggle and three sessions with the HUD goggle under a variety of conditions. The skiing behaviour of each participant was monitored using a Global Positioning System (GPS) tracker. The runs of the ski area were divided into 51 homogeneous run sections and speed quantiles (median to maximum in 5 percentage point intervals) were calculated for each individual pass through these run sections (n=4,451). A mixed-effects model was then applied to examine the effect of HUD goggles on skiing speeds for each quantile in combination with various personal (e.g., skiing ability) and external factors (e.g., terrain). Among the variables tested, ability level had the strongest positive effect on skiing speeds, while terrain characteristics including steep gradients, ungroomed runs, and treed areas, were all associated with slower skiing speeds. No overall long-term effect of HUD goggle use on skiing speeds was found, but advanced/expert skiers did appear to benchmark ‘personal best’ speeds during first HUD use – particularly on long straight run sections – before returning to slower speeds during subsequent HUD use. Whereas no significant HUD effect was observed among beginners/intermediates, skiing speeds were significantly faster among beginners/intermediates listening to music during the sessions. The potential for distraction as a result of HUD use still requires investigation.

Document type: 
Graduating extended essay / Research project
Rights: 
This thesis may be printed or downloaded for non-commercial research and scholarly purposes. Copyright remains with the author.
File(s): 
Supervisor(s): 
Pascal Haegeli
Alison Gill
Department: 
Environment: School of Resource and Environmental Management
Thesis type: 
(Research Project) M.R.M.
Statistics: