Applicability of risky decision-making theory to understand drivers' behaviour during transitions of control in vehicle automation

Decision-making, Behavioural modeling, Automated vehicles. This work presents a consideration of the applicability of risky decision-making theory models as a tool to understand drivers’ take-over behaviour from vehicle automation, while also incorporating the “Out of the Loop” concept and the process of Situation Awareness Recovery. A methodological discussion is provided, and implications for the processes involved in system design developments are presented. Finally, the paper concludes that the process of evidence accumulation in risky decision-making theory models has strong parallels with the process of Situation Awareness recovery. We argue that evidence accumulation models can be used as a tool to understand what information is used by drivers for achieving safe transitions of control from automation so that this knowledge can be used for a better, and more human-centred design of future in-vehicle interfaces. In the end, this paper presents one theoretical model as a practical implementation of the theory discussed in experimental datasets.