Automated driving systems (ADS) and a combination of these with advanced driver assistance systems (ADAS) will soon be available to a large consumer population. Apart from testing automated driving features and human–machine interfaces (HMI), the development and evaluation of training for interacting with driving automation has been largely neglected. The present work outlines the conceptual development of two possible approaches of user education which are the owner’s manual and an interactive tutorial. These approaches are investigated by comparing them to a baseline consisting of generic information about the system function. Using a between-subjects design, N = 24 participants complete one training prior to interacting with the ADS HMI in a driving simulator. Results show that both the owner’s manual and an interactive tutorial led to an increased understanding of driving automation systems as well as an increased interaction performance. This work contributes to method development for the evaluation of ADS by proposing two alternative approaches of user education and their implications for both application in realistic settings and HMI testing.

Within a workshop on evaluation methods for automated vehicles (AVs) at the Driving Assessment 2019 symposium in Santa Fe; New Mexico, a heuristic evaluation methodology that aims at supporting the development of human–machine interfaces (HMIs) for AVs was presented. The goal of the workshop was to bring together members of the human factors community to discuss the method and to further promote the development of HMI guidelines and assessment methods for the design of HMIs of automated driving systems (ADSs). The workshop included hands-on experience of rented series production partially automated vehicles, the application of the heuristic assessment method using a checklist, and intensive discussions about possible revisions of the checklist and the method itself. The aim of the paper is to summarize the results of the workshop, which will be used to further improve the checklist method and make the process available to the scientific community. The participants all had previous experience in HMI design of driver assistance systems, as well as development and evaluation methods. They brought valuable ideas into the discussion with regard to the overall value of the tool against the background of the intended application, concrete improvements of the checklist (e.g., categorization of items; checklist items that are currently perceived as missing or redundant in the checklist), when in the design process the tool should be applied, and improvements for the usability of the checklist.

The development of automated driving will profit from an agreed-upon methodology to evaluate human–machine interfaces. The present study examines the role of feedback on interaction performance provided directly to participants when interacting with driving automation (i.e., perceived ease of use). In addition, the development of ratings itself over time and use case specificity were examined. In a driving simulator study, N = 55 participants completed several transitions between Society of Automotive Engineers (SAE) level 0, level 2, and level 3 automated driving. One half of the participants received feedback on their interaction performance immediately after each use case, while the other half did not. As expected, the results revealed that participants judged the interactions to become easier over time. However, a use case specificity was present, as transitions to L0 did not show effects over time. The role of feedback also depended on the respective use case. We observed more conservative evaluations when feedback was provided than when it was not. The present study supports the application of perceived ease of use as a diagnostic measure in interaction with automated driving. Evaluations of interfaces can benefit from supporting feedback to obtain more conservative results.

Zusammenfassung: Die Veränderung der Fahrerrolle im hochautomatisierten Fahren vom Akteur zum „Passagier am Fahrersitz“ wirft neue Fragen auf nach dem erlebten Fahrkomfort in dieser veränderten Situation. In einer kombinierten Fahrsimulator- und Realfahrstudie wurde der Einfluss von Fahrermerkmalen auf den wahrgenommenen Fahrkomfort, die Akzeptanz und den Fahrspaß im hochautomatisierten Fahren untersucht.

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.