Systematic review evaluates takeover systems for highly automated driving, highlighting design and performance implications.
As vehicle automation advances toward highly automated driving, takeover systems must address scenarios where users are entirely disengaged from the driving task. Although highly automated driving remains largely experimental, designing and researching robust takeover systems is essential for ensuring safe deployment, fostering user trust, and promoting system acceptance. Existing research has explored individual aspects of takeover design and interaction, but a comprehensive synthesis remains lacking. This paper presents a systematic review of 61 studies retrieved from the ACM Digital Library, Web of Science, ScienceDirect, and IEEE Xplore. The review is structured across three core dimensions: (1) takeover system design-including takeover budgets, modalities, and prompt information; (2) takeover scenarios-including driver characteristics, non-driving-related tasks, and traffic environments; and (3) Experimental apparatus and measurement methods used to evaluate driver behaviour and takeover performance. Additionally, this paper highlights inconsistencies in the definitions of automation levels and discusses their implications for comparability and validity in HAD research. Finally, it outlines key directions for future research on HAD takeover systems.
No takes yet. Share an insight, caveat, or question.
Liu et al. (2025) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: