A Survey of Eye Tracking in Automobile and Aviation Studies: Implications for Eye-Tracking Studies in Marine Operations
DOI: 10.1109/thms.2021.3053196
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Summary
This paper presents a systematic survey of eye-tracking research in automobile and aviation sectors to determine how these methodologies can be transferred to marine operations. The primary motivation is the need to address human error, which is a critical safety concern in marine industries such as offshore petroleum extraction and wind turbine installation. While eye tracking is widely used in driving and flying to evaluate operational effectiveness and mental workload, systematic guidelines for its application in marine contexts remain sparse. The authors aim to bridge this gap by analyzing existing literature to provide actionable instructions for defining Areas of Interest (AOIs) and designing experiments for marine operators. The study employs a systematic literature review guided by the PRISMA statement, analyzing papers published between 2010 and 2020. The authors categorized the selected studies based on several characteristics, including stimulus type (static vs. dynamic), visualization methods, scenario type (simulated vs. real), and participant expertise. A central focus of the analysis is the method used to define AOIs, which the authors identify as a key distinction among studies. They classify AOI definition methods into four categories: expert-defined, stimulus-generated, attention-map defined, and clustering-algorithm defined. The review also examines experimental procedures, participant demographics, and the frequency of specific eye-metric data and visualization techniques used in the surveyed papers. The findings reveal that AOI-based stimuli are more prevalent than point-based stimuli in both automobile and aviation studies, reflecting the importance of spatial focus in these tasks. The authors detail the conditions and processing steps for each AOI definition method. For instance, expert-defined AOIs are common when high fixation density areas cannot be predicted in advance, while stimulus-generated AOIs are used when specific visual boundaries are clear. Attention maps and clustering algorithms are utilized when stimuli lack clear separation boundaries. The analysis shows that automobile studies favor attention maps for visualizing fixation density, whereas aviation studies prefer scanpaths to show spatial distribution. Participant numbers and ages were similar across both fields, with mean participant counts around 26 and mean ages between 32 and 33. The significance of this work lies in its provision of a framework for transferring eye-tracking knowledge to marine operations. The authors conclude that similarities in simulator use, experimental design, and AOI types (e.g., control panels and external views) facilitate this knowledge transfer. They provide specific guidelines for selecting AOI definition methods and experimental procedures tailored to marine scenarios. To demonstrate effectiveness, the paper applies these findings to a case study of a heavy-lifting marine operation. By establishing these guidelines, the study aims to improve the assessment of human error and operational safety in marine environments, leveraging the mature methodologies established in automobile and aviation research.
Provenance
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | OpenAlex-citations | — | — | 1 | 2026-06-17 |
| archive | success | unpaywall | — | — | 2 | 2026-06-25 |
| extract | success | cached | — | — | 2 | 2026-06-25 |
| clean | success | clean | — | — | 1 | 2026-06-18 |
| chunk | success | chunk | — | — | 1 | 2026-06-18 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-18 |
| promote | success | — | — | — | 1 | 2026-06-17 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 1 | 2026-06-25 |
| tag | success | vector_similarity | — | — | 6 | 2026-06-18 |
| verify | success | — | — | — | 1 | 2026-06-26 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-25; verification: verified.
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