This research presents a risk-informed framework to derive metrics characterizing and tracking the safety performance of heavy-duty automated vehicles (HD-AVs) operations. A combination of traditional and novel hazard identification methods are leveraged to study potential human-system interactions in HD-AVs operations, ranging from safety drivers to remote operators.
