Estimating How Long In-Vehicle Tasks Take: Static Data for Distraction and Ease-of-Use Evaluations 2024-01-2505

Often, when assessing the distraction or ease of use of an in-vehicle task (such as entering a destination using the street address method), the first question is “How long does the task take on average?” Engineers routinely resolve this question using computational models. For in-vehicle tasks, “how long” is estimated by summing times for the included task elements (e.g., decide what to do, press a button) from SAE Recommended Practice J2365 or now using new static (while parked) data presented here. Times for the occlusion conditions in J2365 and the NHTSA Distraction Guidelines can be determined using static data and Pettitt’s Method or Purucker’s Method. These first approximations are reasonable and can be determined quickly.

The next question usually is “How likely is it that the task will exceed some limit?” This question, addressed using discrete event simulations such as IMPRINT, requires the distribution types and parameters (mean, standard deviation, etc.) for each task element, data which generally are not available in the published literature for in-vehicle tasks (e.g., SAE J2365). Those distribution types and parameters are presented here, derived from further analyses of the data for 13 static task elements in Green et al. (2015). For example, for static task times, the time to press a function key could be modeled as Normal (2.36, 2.61) or Weibull with a Threshold (3.94, 1.52, -0.62). If only mean task element times are available in the chosen dataset, the standard deviations could be estimated as (0.77*mean time) + 0.12 for static conditions.