Methodological Approach towards Evaluating the Effects of Non-Driving Related Tasks during Partially Automated Driving

Abstract

Partially automated driving (PAD, Society of Automotive Engineers (SAE) level 2) features provide steering and brake/acceleration support, while the driver must constantly supervise the support feature and intervene if needed to maintain safety. PAD could potentially increase comfort, road safety, and traffic efficiency. As during manual driving, users might engage in non-driving related tasks (NDRTs). However, studies systematically examining NDRT execution during PAD are rare and most importantly, no established methodologies to systematically evaluate driver distraction during PAD currently exist. The current project’s goal was to take the initial steps towards developing a test protocol for systematically evaluating NDRT’s effects during PAD. The methodologies used for manual driving were extended to PAD. Two generic take-over situations addressing system limits of a given PAD regarding longitudinal and lateral control were implemented to evaluate drivers’ supervisory and take-over capabilities while engaging in different NDRTs (e.g., manual radio tuning task). The test protocol was evaluated and refined across the three studies (two simulator and one test track). The results indicate that the methodology could sensitively detect differences between the NDRTs’ influences on drivers’ take-over and especially supervisory capabilities. Recommendations were formulated regarding the test protocol’s use in future studies examining the effects of NDRTs during PAD.

Editorial for Special Issue: Test and Evaluation Methods for Human-Machine Interfaces of Automated Vehicles

“…The second paper "Methodological Approach towards Evaluating the Effects of Non-Driving Related Tasks during Partially Automated Driving" by Hollander, Rauh, Naujoks, Hergeth, Krems and Keinath [14] shows the development of a test protocol for systematically evaluating non driving-related tasks' (NDRT) effects during partially automated driving (PAD). Two generic take-over situations addressing system limits of a given PAD regarding longitudinal and lateral control were implemented to evaluate drivers' supervisory and take-over capabilities while engaging in different NDRTs (e.g., manual radio tuning task).…”

How to Keep Drivers Attentive during Level 2 Automation? Development and Evaluation of an HMI Concept Using Affective Elements and Message Framing

“…[15] predicts a high rate of unsafe outcomes in plausible automation failure scenarios, Ref. [16] reports that more distractive NDRAs result in impaired take-over capabilities, and past accidents with Tesla Autopilot [3] or the Uber car [17] are examples of these risks that have the potential to counteract the expected positive effects of automation on traffic safety and may thus negatively shape the image of this technology. Furthermore, the perception of a lack of safety creates reluctance towards the use of automated driving functions and the behavioral intention to use [18].…”