Investigating the impact of factors related to driver distraction and traffic behaviors (Case study: Qazvin Province in 1403)

Document Type : Original Article

Authors
Shahab Hassanpour 1
Seyyed Teymoor Hosseini 2
Hossein Taghi khani 3
1 Assistant Professor, Department of Civil Engineering, Ayatollah Borujerdi University, Borujerd, Iran.
2 Associate Professor, Amin University, Tehran, Iran.
3 Ph.D., Student, Amin University, Tehran, Iran.
10.22034/road.2025.538778.2421
Abstract
The present study was descriptive-correlational and conducted by survey method. The statistical population included active drivers in Qazvin province. Using simple random sampling, 600 questionnaires were distributed and finally 486 complete questionnaires were collected and analyzed. The data collection tool was the Feng et al. standard questionnaire including demographic and behavioral variables related to driving and the Manchester standard questionnaire including distraction variables. Multiple regression was used simultaneously in SPSS software to analyze the data. Findings: The research findings showed that there is a significant relationship between different components of driving behavior (slips, intentional violations, errors and unintentional violations) and driver distraction. The results of multiple regression analysis showed that errors with a standard coefficient of Beta = 0.388 have the highest predictive power of distraction. Following that, unintentional violations, intentional violations and slips also played a role in the model, but with a lower impact intensity. Also, examining the distribution of residuals and the collinearity test showed the adequacy of the model and the absence of statistical problems in estimating the relationships. Using a mobile phone while driving and a history of accidents are the most important factors in increasing distraction among drivers. In contrast, increasing education and driving experience can lead to a decrease in distraction. These findings reinforce the need for targeted education and policymaking to reduce risk-causing behavioral factors.
Keywords
Distraction
traffic driving behavior
multiple regression
mobile phone
Qazvin province
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