About this Research Topic
Autonomous vehicles (AVs) have great societal benefits. However, the road to reliable AVs is still long. In the meantime, Teleoperation has been proposed as a solution that can allow more rapid adoption of imperfect AVs. Teleoperators are human operators who can remotely connect and control an AV when on-board system cannot perform well. Teleoperators face numerous challenges including situation awareness, latency, managing AV capabilities, etc. To meet these challenges, they need to apply spatial perception, state awareness, decision making and other cognitive functions.
Human factors in teleoperation is an emerging research area. Specifically, three tracks have characterized recent studies: The first is tracking the teleoperator state. Today’s sensors can detect useful indices such as head position, gaze, respiration rate, heart rate, and skin conductance to infer fatigue, workload, distraction, etc. These data can serve as useful information for researchers, feedback to teleoperators, monitoring tools for teleoperation center managers, and as input for automated systems that consider the teleoperator state in their decisions.
The second track is teleoperator interfaces. Depending on the task, controlling a remote AV can involve varied control modes (from manual to supervisory control), input devices, and feedback displays.. While the variety of interfaces may improve performance, using these interfaces effectively, and switching between modes and features requires expertise and training. Hence, they present challenges for Teleoperators, designers, and engineers.
The third track is designing Advanced Teleoperator Assistance Systems (ATAS), which offers decision support tools (trajectory planning, hazard detection, etc.) as well as automated capabilities for operating the vehicle. However, there are still challenges, as operators are required to develop strategies for managing ATAS and responding when these tools fail. In these situations, sharing and coordinating control becomes a major interaction design challenge. Issues of situation awareness, taking initiative, and taking responsibility are rich areas for research. Organizational and cultural issues are also important for understanding how teleoperators will interact and perform with increasingly autonomous systems.
As part of the recent innovative research tracks, new challenges for teleoperator performance should be studied; existing models should be reevaluated, technology-based interventions should be assessed, and measures to evaluate teleoperators' performance should be developed.
This Research Topic will focus on research that can promote the development of tools to train Teleoperators, assess their ability, and monitor their performance. Manuscripts related to methods for allocating tasks for Teleoperators, novel interfaces and systems for controlling AVs, and advanced task allocation systems are welcome. We encourage researchers from different disciplines to submit empirical studies. We also welcome reviews, meta-analyses, and commentaries on these issues.
Specific topics include but are not limited to:
• Development of new models of teleoperator performance;
• Technology-based interventions to improve teleoperator performance;
• Sensor-based methods (e.g., physiological sensors, contact-free sensing systems) to monitor teleoperator states;
• Challenges in teleoperator - ATAS interaction;
• Naturalistic teleoperation studies;
• Methods to allocate tasks to teleoperators according to their state and skills;
• Interfaces for teleoperators.
Keywords: Teleoperator performance, Teleoperator state, Indices for teleoperator monitoring, Advanced Teleoperation Assistance Systems, Interfaces for Teleoperation, Human-in-the-loop, Shared Control, Robot Operators, Human-Robot Interaction
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.