Driving Fine and its Relationship with Dangerous Driving Behaviour among Heavy Vehicle Drivers

Driving Fine and its Relationship with Dangerous Driving Behaviour among Heavy Vehicle Drivers

Code: G-04897

Authors: Masoud Motalebi Kashani, Hossein Akbari, Hamid Reza Saberi, Reihaneh Ghorbani Pour, Fahimeh Karamali © ℗, Masoomeh Sadat Shamsi

Schedule: Not Scheduled!

Tag: Safety

Download: Download Poster

Abstract:

Background and Aim

There is a significant difference between actual and existing statistics of traffic fines; since some invisible fines and most of the visible traffic violations cannot be recorded by traffic officers. Therefore, dealing with driving fines and road fatalities is considered an important issue in social and public management worldwide. Explore the factors associated with unsafe behaviors and getting traffic fines among a sample of Iranian heavy vehicle professional drivers.

Method

The present cross sectional study was conducted in Iran, from February 2019 to September 2020. The sample size was determined based on observed variables. The main instrument of the study was a questionnaire consisting of 32 items to measure the observed variables of this study. This study used the driver behavior questionnaire (DBQ), demographic and driving characteristics, the number of fines, and structural equation modeling. Also, in this study 320 professional drivers participated. Demographic information Several questions about drivers’ driving and demographic characteristics were provided in the first section of the questionnaire. The Iranian 15‑item modified DBQ based on the original DBQ developed by was used to evaluate risky driving behaviors. To investigate the participants’ characteristics, descriptive statistics were applied, and to determine the inter‑correlations among the variables, bivariate Pearson correlation analysis was run. This article used structural equation modeling for Statistical analysis.

Results

The results of structural equation modeling analysis indicated that the data fit well with the theoretical model proposed in this study. The number of fines was directly predicted by both demographic and driving characteristics and risky driving behaviors. A significant relationship was observed between, driving hours, driving experience, and smoking, respectively, with a mistake, slip, and risky violation. There was a negative correlation between education and all four sub scales of risky driving behaviors. It was revealed that the direct effects of the seven demographic and driving characteristics on traffic fines were not significant; whereas Driver’s educational level (indirect effect = ‑0.075),Years of experience (indirect effect = ‑0.023) exerted a negative and indirect influence on traffic fines via driving behaviors. Questionnaire was very reliable and can be utilized for the structural equation modeling.

Conclusion

The main factors of the driver to get involved in traffic violation and dangerous driving behavior, are as follows: driver × s education level, driver’s age and experience, hours of driving (d) driver × s smoking habit, slip. In order to reduce traffic fines, training courses on increasing attention and precision in drivers’ observations and judgments are useful. The courses can decrease traffic violations by trying to change beliefs, attitudes, and social norms. It is

Keywords

Aberrant driving behaviors, professional drivers, structural equation modeling, traffic fines

Post comment is closed by admin.