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After activation of a Society of Automotive Engineers (SAE) Level 3 automated driving function (SAE International, 2021), the function takes over the driving task and the human user may engage in other, non-driving-related tasks (NDRTs). Meanwhile, the user needs to remain receptive to requests by the function because s/he needs to reengage in the driving task, when the function approaches a system limit and requests the user to take over. Hence, the effects of NDRT engagement on driver state and takeover behavior have been investigated closely. However, concerning relevance to traffic safety, it is important to take a step back and investigate what NDRTs users are likely to engage in, and what methods are suitable to collect respective data. Two experiments were conducted to answer these questions. In Experiment 1, participants experienced Level 3 automated driving in a Wizard-of-Oz vehicle on German motorways. After the ride, participants were asked to name NDRTs that they would engage in, if the function was available in their own vehicle. In Experiment 2, participants were asked to bring their own NDRTs along and experienced Level 3 automated driving in the Wizard-of-Oz vehicle. Comparison of results shows preferences of similar NDRTs (e.g., smartphone usage and reading). Moreover, we found that different methods provide different insights into NDRT engagement (i.e., engagement rate, total duration rate of engagement, and naming rate). Integrating our results in current literature landscape highlights the strong dependence of resulting NDRTs from the investigation method. Results, strengths, and weaknesses of the employed methods are discussed.

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Since users of Level 3 driving automation systems may engage in non-driving related activities, it is of interest to investigate effects of non-driving related activities on traffic safety. The current meta-analysis aims at estimating non-driving related activities’ effects on takeover behavior based on theory and empirical findings on task switching and modality shifting. Results indicate that takeover time increases after non-driving related activities that (1) physically require the user to free his/her hands from the respective activity before takeover, (2) obstruct concurrent visual perception of the driving environment, (3) are dissimilar to the driving task in terms of required cognitive processing modules.

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