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In SAE (Society of Automotive Engineers) Level 2, the driver has to monitor the traffic situation and system performance at all times, whereas the system assumes responsibility within a certain operational design domain in SAE Level 3. The different responsibility allocation in these automation modes requires the driver to always be aware of the currently active system and its limits to ensure a safe drive. For that reason, current research focuses on identifying factors that might promote mode awareness. There is, however, no gold standard for measuring mode awareness and different approaches are used to assess this highly complex construct. This circumstance complicates the comparability and validity of study results. We thus propose a measurement method that combines the knowledge and the behavior pillar of mode awareness. The latter is represented by the relational attention ratio in manual, Level 2 and Level 3 driving as well as the controllability of a system limit in Level 2. The knowledge aspect of mode awareness is operationalized by a questionnaire on the mental model for the automation systems after an initial instruction as well as an extensive enquiry following the driving sequence. Further assessments of system trust, engagement in non-driving related tasks and subjective mode awareness are proposed.

Future vehicles will combine different levels of capable driving automation characterized by varying responsibilities for users. This development will lead to an increase in system complexity which poses the risk of confusing the driver. Based on the theory of proactive interference, we hypothesize that the users’ mode awareness suffers especially when changing from Level 3 “Conditional Automation” to Level 2 “Partial Automation”. Consequently, a mode transition intermitted by a short phase of manual driving acts as a countermeasure for a loss of mode awareness. Assumptions were tested in a driving simulator study with 45 valid participants. Mode awareness was operationalized by the visual attention towards driving-relevant areas and a qualitative analysis of an interview. Results indicate that in partial automation, visual attention does not deteriorate due to a lack of mode awareness, but rather to the development of overreliance arising from the experience with a very reliable partially automated system.