Remote driving is a promising strategy for helping Autonomous Vehicles (AVs) navigate many environments where edge cases may otherwise limit their abilities. For some companies, remote driving is an alternative to AVs altogether. Much remote driving research has taken place in simulated or controlled environments with novice operators, leaving the needs of operators with real-world experience under-explored. This research aims to understand if experienced operators are satisfied with current production remote driving systems, if they adapt to the difference in control, and how their job satisfaction compares to in-vehicle safety driving. This paper briefly overviews recent remote driving research and presents results from a questionnaire and a semi-structured interview with experienced teleoperators. The findings indicate that operators do adjust to the new domain, but latency and network reliability remain a challenge. Likewise, standardised training practices for operators are found to be lacking.

Prior work suggests that the potential benefits of mixed initiative management of multiple robots are mitigated by situational factors, including workload and operator expertise. In this paper, we present an experiment where allowing a supervisor and group of searchers to jointly decide the correct level of autonomy for a given situation ("mixed initiative") results in better overall performance than giving an agent exclusive control over their level of autonomy ("adaptive autonomy") or giving a supervisor exclusive control over the agent's level of autonomy ("adjustable autonomy"), regardless of the supervisor's expertise or workload. In light of prior work, we identify two elements of our experiment that appear to be requirements for effective mixed initiative control of large-scale robotic teams: (a) Agents must be capable of making progress toward a goal without having to wait for human input in most circumstances. (b) The operator control interface must help the human to rapidly understand and modify the progress and intent of several agents.