Keywords: Situational Awareness Grounding Methods, Assistive Driving, VR Driving Simulation
TL;DR: We propose a novel interactive protocol for acquiring dense continuous driver situational awareness labels for objects in their field-of-view, without affecting their natural gaze behaviour.
Abstract: Commonly used protocols for capturing the ground-truth situational awareness (SA) of drivers involve halting a simulation and querying the driver. SA data collected in this way is unsuitable for training models for predicting real-time SA since it is inherently intermittent and does not capture transitions of SA (e.g. from not aware to aware). We introduce an efficient VR based interactive protocol designed to capture a driver's ground-truth situational awareness (SA) in real time. Our protocol mitigates the aforementioned limitations of prior approaches, and allows capturing continuous object-level SA labels that are more suitable for downstream real-time SA prediction tasks. Our initial findings highlight its potential as a scalable solution for curating large scale driving datasets with ground-truth SA.
Submission Number: 5
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