Integration of Human Factors in an Automated Driving Supervision System
DOI: 10.54941/ahfe1002308
archive: archived pipeline: cataloged verified
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Summary
This paper addresses the under-researched area of remote supervision for autonomous vehicles (AVs), aiming to design an anthropocentric centralized command center. While driver takeover and safety issues are widely studied, the authors argue that remote supervision, similar to systems in aviation and railways, could enhance safety by anticipating incidents, managing system failures, and ensuring network regularity. The study is motivated by the need to integrate human factors into AV supervision systems before their deployment, using a prospective ergonomics approach to anticipate future work situations where the technology is not yet mature. The methodology employs the "possible future activity" approach, utilizing reference situations from existing sectors to inform the design of future AV supervision. The authors identified eight activity sectors based on two central functions: supervision/monitoring and remote driving/control. Data collection focused on three fully analyzed fields: bus and tramway supervision, civil air traffic control, and military air traffic control, with a fourth field (logistics drones) under exploratory study. The researchers used Core Task Analysis, involving open observations of real work, semi-structured interviews with seven operators, and critical incident analysis. Interviews covered themes such as core tasks, professional skills, communication, user interfaces, and relationships with automation. The results highlight significant differences in supervision modalities and organizational structures across sectors. Air traffic control is characterized by "proactive supervision," where controllers centrally coordinate aircraft, whereas bus and tramway sectors employ "reactive supervision," where regulators resolve conflicting situations. Workstation organization also differs: air transport uses booths with two agents (controller and planner), while land transport uses single-agent workstations. Safety cultures vary, with aviation featuring rigorous post-incident analysis and formal workload distribution strategies (e.g., sector subdivision based on aircraft count), whereas land transport lacks formal workload distribution, relying on informal support during overload. Both sectors utilize real-time visualization software, but task allocation differs; aviation systems provide alerts for trajectory conflicts without proposing maneuvers, while land transport supervisors desire software aids for repositioning vehicles after incidents. The significance of this work lies in establishing a preliminary basis for designing AV supervision systems by extracting crucial information about organization, functioning, and vigilance from diverse sectors. The authors conclude that while the macro function of supervisors is to provide a global vision, their specific roles vary significantly, reflected in titles like "regulator" versus "controller." These findings will inform creativity workshops to define system specifications, focusing on needs, functions, and solutions. The study underscores the importance of considering human cognitive limits, trust, and situational awareness in the design of future human-machine cooperative systems for autonomous mobility.
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-08-09 |
| archive | success | canonical_url | — | — | 1 | 2026-08-09 |
| extract | success | pdftotext | — | — | 4 | 2026-08-10 |
| clean | success | clean | — | — | 2 | 2026-08-10 |
| chunk | success | chunk | — | — | 2 | 2026-08-10 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 2 | 2026-08-10 |
| promote | success | — | — | — | 1 | 2026-08-09 |
| summarize | success | llm | qwen3.6-27b-nvidia | summ-v5 | 2 | 2026-08-10 |
| tag | success | vector_similarity | — | — | 17 | 2026-08-11 |
| verify | partial | — | — | — | 2 | 2026-08-10 |
Summary generated by qwen3.6-27b-nvidia on 2026-08-10; verification: verified_with_issues.
Topics
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- automation complacency bias
- automation
- automation surprise
- driverless ads
- teleoperation remote driving
- mode awareness
Information type
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- Theoretical Contribution: conceptual framework, theory or model