Analyzing Vehicle Operator Deviations

Pounds, Julia; Bailey, Larry; Scarborough, Alfretia · 2008 · ROSA P / Civil Aeromedical Institute

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Summary

This study addresses the under-researched human factors contributing to Vehicle Operator Deviations (VODs), a significant safety concern for the Federal Aviation Administration (FAA). While runway incursions involving pilots and air traffic controllers are well-documented, little is known about deviations caused by ground vehicles entering airport movement areas without approval. The authors aimed to develop and validate a predictive model for VODs and improve the reporting process by adapting the JANUS-ATC human error taxonomy to ground operations, creating JANUS-GRO. The researchers analyzed archival data from the National Aviation Incident Monitoring System (NAIMS) covering 996 VODs between January 2002 and May 2006. Due to incomplete reporting, only 229 cases with sufficient data were used for statistical analysis. The study tested six hypotheses regarding the relationships between training, airport access authorization, contextual conditions, mental processes, and VOD types using logistic regression. Additionally, directed graphical modeling via the WinMine toolkit was employed to identify causal sequences among variables. The authors also mapped existing FAA reporting forms (8020-24 and 8020-25) onto the JANUS-GRO framework to evaluate the comprehensiveness of current data collection. The results provided partial support for the hypothesized model. Logistic regression indicated that vehicle operators authorized for the movement area were significantly more likely to complete driver training and commit deviations related to following ATC instructions, particularly when they believed they had clearance. Conversely, operators unauthorized for the movement area were significantly more likely to fail to observe signs, markings, or lighting. Mental process analysis revealed that being lost was associated with unauthorized operators, while distraction was linked to authorized ones. Directed graphical modeling identified a causal chain where a lack of knowledge regarding airport layout led to operators becoming lost or unable to locate routes, even after completing training. Crucially, the mapping of reporting forms revealed that 56.1% of collected data was purely descriptive, and only 3.7% addressed mental processes, highlighting a severe deficit in capturing underlying human factors. The study concludes that current VOD reporting processes are inadequate for identifying root causes, as they emphasize contextual descriptions over human factors analysis. The authors recommend adopting the JANUS-GRO taxonomy to standardize reporting, thereby enabling better identification of trends, design of mitigation strategies, and evaluation of safety initiatives. By capturing detailed information on mental processes and organizational influences, the FAA and airport authorities can more effectively address the human factors driving vehicle operator deviations.

Key finding

Vehicle operators authorized for movement area access were significantly more likely to commit deviations by failing to follow other ATC instructions, whereas unauthorized operators were more likely to fail to observe signs, markings, signals, or lighting.

Methodology

dataset

Sample size: 229

Provenance

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

Topics

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• pre crash contributing factors
• human error taxonomy

Information type

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• Theoretical Contribution: theory or model