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Associate Professor, School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran. , kayvan.aghabayk@ut.ac.ir
Abstract: (33 Views)
Background: Road crashes are one of the most serious and ongoing challenges worldwide, leading to extensive human and financial losses. Although several factors contribute to road crashes, human factors particularly risky driving behaviors and their psychological aspects are recognized as key components in determining road safety levels. In Iran, there is a notable research gap due to the lack of comprehensive and targeted studies specifically addressing risky driving behaviors and the factors influencing them.
Aims: This study aimed to identify and categorize the risky driving behaviors of Iranian drivers based on their self-reported views.
Methods: The statistical population of this study comprises all the drivers in the country, selected through random sampling. To achieve this, risky driving behaviors were first identified based on previous studies and common behaviors among Iranian drivers. Subsequently, a questionnaire covering personal information, risky driving behaviors, and drivers' crash records was designed and distributed online across Iran. After initial evaluations, the responses from 2,387 drivers were subjected to final analysis using a quantitative method.
Results: The results of the exploratory factor analysis performed on the data showed that risky driving behaviors can be divided into five main categories: Negligent and noncompliant driving, distracted driving, aggressive driving, speeding, driving in extreme conditions. A positive and significant correlation was also observed between the dimensions of risky driving behaviors (P< 0.05), indicating the tool's appropriate concurrent validity. The reliability of the tool was calculated using Cronbach's alpha, with values for all five factors exceeding 0.7, demonstrating good reliability.
Conclusion: This study aims to identify and analyze risky driving behaviors among Iranian drivers to provide a scientific basis for designing psychological interventions and formulating preventive policies. The findings of this research can contribute to improving road safety and reducing crashes in the country.
Aims: This study aimed to identify and categorize the risky driving behaviors of Iranian drivers based on their self-reported views.
Methods: The statistical population of this study comprises all the drivers in the country, selected through random sampling. To achieve this, risky driving behaviors were first identified based on previous studies and common behaviors among Iranian drivers. Subsequently, a questionnaire covering personal information, risky driving behaviors, and drivers' crash records was designed and distributed online across Iran. After initial evaluations, the responses from 2,387 drivers were subjected to final analysis using a quantitative method.
Results: The results of the exploratory factor analysis performed on the data showed that risky driving behaviors can be divided into five main categories: Negligent and noncompliant driving, distracted driving, aggressive driving, speeding, driving in extreme conditions. A positive and significant correlation was also observed between the dimensions of risky driving behaviors (P< 0.05), indicating the tool's appropriate concurrent validity. The reliability of the tool was calculated using Cronbach's alpha, with values for all five factors exceeding 0.7, demonstrating good reliability.
Conclusion: This study aims to identify and analyze risky driving behaviors among Iranian drivers to provide a scientific basis for designing psychological interventions and formulating preventive policies. The findings of this research can contribute to improving road safety and reducing crashes in the country.
Keywords: risky driving behaviors, crashes, questionnaire, traffic safety, Psychological interventions
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This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) License. |
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)