Human behaviour with automated driving systems: a quantitative framework for meaningful human control

Abstract Automated driving systems (ADS) with partial automation are currently available for the consumer. They are potentially beneficial to traffic flow, fuel consumption, and safety, but human behaviour whilst driving with ADS is poorly understood. Human behaviour is currently expected to lead to dangerous circumstances as ADS could place human drivers ‘out-of-the-loop’ or cause other types of adverse behavioural adaptation. This article introduces the concept of ‘meaningful human control’ to better address the challenges raised by ADS, and presents a new framework of human control over ADS by means of literature-based categorisation. Using standards set by European authorities for driver skills and road rules, this framework offers a unique, quantified perspective into the effects of ADS on human behaviour. One main result is a rapid and inconsistent decrease in required skill- and rule-based behaviour mismatching with the increasing amount of required knowledge-based behaviour. Furthermore, the development of higher levels of automation currently requires different human behaviour than feasible, as a mismatch between supply and demand in terms of behaviour arises. Implications, discrepancies and emerging mismatches this framework elicits are discussed, and recommendations towards future design strategies and research opportunities are made to provide a meaningful transition of human control over ADS.