Identification and Assessment of Human Error for Car Driver using CREAM Technique
Author(s):
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
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.Keywords:
Language:
Persian
Published:
Journal of Occupational Hygiene Engineering, Volume:5 Issue: 3, 2018
Pages:
63 to 75
https://www.magiran.com/p1957534
سامانه نویسندگان
مقالات دیگری از این نویسنده (گان)
-
A Scoping Review of Theses and Dissertations on Pedestrian Crossing Behavior: A Cross-Country Comparison of Key Features
Mohammadsaber Parvand, Fatemeh Ghalandari, Roghayeh Naghdi, Shahin Amini, *
Health Education and Health Promotion, Summer 2024 -
Are Demographic Characteristics Able to Predict Risky Behaviors of Pedestrians?
Anahita Abbaspour, Khadijeh Hajimiri, *
Journal of Human Environment and Health Promotion, Winter 2023