Exploring Human-Autonomy Teams in Automated Driving System Operations

Advancing our understanding of human-autonomous system collaboration is a critical task for the safer design of complex socio-technical systems. The adoption of Automated Driving Systems (ADS) in mobility services and in individually owned vehicles is projected to have a major impact on the transportation environment. From a safety and risk assessment perspective, it is of interest to define, model and assess the interactions, collaborations, and teaming that can occur between human and autonomous agents in ADS operations. This work draws from the cognitive model Information, Decision, and Action in Crew context (IDAC) to explore interactions and errors across different teams in ADS contexts. Two cases of Human-Autonomy Teams (HATs) are discussed, focusing on remote operators and on-board drivers collaborating with ADS-equipped vehicles.