Modelling Automation–Human Driver Handovers Using Operator Event Sequence Diagrams

Abstract

This research aims to show the effectiveness of Operator Event Sequence Diagrams (OESDs) in the normative modelling of vehicle automation to human drivers’ handovers and validate the models with observations from a study in a driving simulator. The handover of control from automation to human operators has proved problematic, and in the most extreme circumstances catastrophic. This is currently a topic of much concern in the design of automated vehicles. OESDs were used to inform the design of the interaction, which was then tested in a driving simulator. This test provided, for the first time, the opportunity to validate OESDs with data gathered from videoing the handover processes. The findings show that the normative predictions of driver activity determined during the handover from vehicle automation in a driving simulator performed well, and similar to other Human Factors methods. It is concluded that OESDs provided a useful method for the human-centred automation design and, as the predictive validity shows, can continue to be used with some confidence. The research in this paper has shown that OESDs can be used to anticipate normative behaviour of drivers engaged in handover activities with vehicle automation in a driving simulator. Therefore, OESDs offer a useful modelling tool for the Human Factors profession and could be applied to a wide range of applications and domains.

Investigating Levels of Remote Operation in High-Level On-Road Autonomous Vehicles using Operator Sequence Diagrams

“…OSD's are usually created by using data from scenario observation, interviews and HTA's (Stanton, et al, 2013) and validated by comparing to drivers completing simulations of the scenarios and identifying the number of 'hits', 'misses', 'false alarms', and 'correct rejections' (Stanton, et al, 2021) with a similar method using an on-the-road environment (Stanton, et al, 2022b). In the OSDs the AV user is treated as acting 'perfectly' in all instances, but this will not always be the case and may impact the resolution process.…”

“…This suggests that OSDs are also a suitable method for predicting the relationships between agents in a remote operation context, where there is limited information on how the scenario may develop in detail (Banks, et al, 2014). More recent papers have also utilised OSDs to model vehicle automation to human driver handover, with validation showing reasonable con dence in the results produced from this method (Stanton, et al, 2021).…”