Effects of Temporal Load on Attentional Engagement: Preliminary Outcomes with a Change Detection Task in a VR Setting

Situation awareness in driving involves detection of events and environmental changes. Failure in detection can be attributed to the density of these events in time, amongst other factors. In this research, we explore the effect of temporal proximity, and event duration in a change detection task during driving in VR. We replicate real-world interaction events in the streetscape and systematically manipulate temporal proximity among them. The results demonstrate that events occurring simultaneously deteriorate detection performance, while performance improves as the temporal gap increases. Moreover, attentional engagement to an event of 5-10 sec leads to compromised perception for the following event. We discuss the importance of naturalistic embodied perception studies for evaluating driving assistance and driver’s education.