Volume 5, Issue 3 (Autumn 2018)
johe 2018, 5(3): 63-75 |
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Najafi Z, Arghami S. Identification and Assessment of Human Error for Car Driver using CREAM Technique. johe 2018; 5 (3) :63-75
URL: http://johe.umsha.ac.ir/article-1-460-en.html
URL: http://johe.umsha.ac.ir/article-1-460-en.html
1- Zanjan University of Medical Sciences
2- Zanjan University of Medical Sciences , arghami@zums.ac.ir
2- Zanjan University of Medical Sciences , arghami@zums.ac.ir
Abstract: (4868 Views)
Introduction: Road accidents are among the major problems of road transportation in Iran. There are four factors involved in road accidents, including human, road, vehicle, and environment. Among these, human (driver) error has an important role in 70-90% of the accidents. Therefore, the present study was aimed at identifying and examining driver errors using the Cognitive Reliability Error Analysis Method.
Methods: A descriptive, cross-sectional design was used to examine a specific scenario involving driving tasks. First, using the Hierarchical task analysis, the driving tasks for the scenario were analyzed. Then, using the primary and broad CREAM techniques, possible driver controls and cognitive errors were determined for the tasks.
Results: Analysis of the scenario using the primary CREAM technique revealed nine diver tasks, including wearing a seat-belt, controlling the indicators, acceleration changing, direction changing, adjusting the distance, stopping the car, turning off the car, unbuckling the seat belt, and the light type of tactical control. Then, using the broad CREAM technique, the execution (71.87%), observation (18.75), and Interpretation (9.38%) errors were determined.
Conclusion: Using the primary technique, four cases of performance-reducing conditions were identified. In General, according to the broad CREAM technique, 32 driver errors were identified. The most common cognitive errors included execution and observation errors. It can be concluded that based on the proposed controls, the risk of human error can be reduced for the analyzed subtasks.
Methods: A descriptive, cross-sectional design was used to examine a specific scenario involving driving tasks. First, using the Hierarchical task analysis, the driving tasks for the scenario were analyzed. Then, using the primary and broad CREAM techniques, possible driver controls and cognitive errors were determined for the tasks.
Results: Analysis of the scenario using the primary CREAM technique revealed nine diver tasks, including wearing a seat-belt, controlling the indicators, acceleration changing, direction changing, adjusting the distance, stopping the car, turning off the car, unbuckling the seat belt, and the light type of tactical control. Then, using the broad CREAM technique, the execution (71.87%), observation (18.75), and Interpretation (9.38%) errors were determined.
Conclusion: Using the primary technique, four cases of performance-reducing conditions were identified. In General, according to the broad CREAM technique, 32 driver errors were identified. The most common cognitive errors included execution and observation errors. It can be concluded that based on the proposed controls, the risk of human error can be reduced for the analyzed subtasks.
Type of Study: Research Article |
Subject:
Safety
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