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Game Engine-based simulators as human reliability data collecting tools: A refinery case

Author

Listed:
  • Caio Bezerra Souto Maior
  • Marcos Vinicius Pinto de Andrade
  • Márcio das Chagas Moura
  • Isis Didier Lins

Abstract

Human behavior has become a significant concern in almost every economic activity. Human errors are on the top accident list, leading to death tolls, material losses, and environmental damages. The lack of large and good-quality datasets for Human Reliability Assessment (HRA) studies is still a problem in applications of safety sciences, and the present work proposes an approach to collecting HRA data from simulator utilizing Game Engines (GE) 3D-Virtual Environments (VE). As validation, an experiment was conducted for an Oil and Gas refinery evacuation scenario under toxic cloud release, with a detailed description of environmental development. Two variables were analyzed: evacuation time and individual risk exposure. Then, a Bayesian Belief Network (BBN) was created to investigate the tool for HRA, considering variables related to training, visibility, and complexity. The study provides valuable insights into human behavior and the generation of datasets, representing a helpful tool for data collection.

Suggested Citation

  • Caio Bezerra Souto Maior & Marcos Vinicius Pinto de Andrade & Márcio das Chagas Moura & Isis Didier Lins, 2026. "Game Engine-based simulators as human reliability data collecting tools: A refinery case," Journal of Risk and Reliability, , vol. 240(3), pages 978-991, June.
    • Handle: RePEc:sae:risrel:v:240:y:2026:i:3:p:978-991
    DOI: 10.1177/1748006X261423238
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