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Assessing the Road Traffic Crashes among Novice Female Drivers in Saudi Arabia

Author

Listed:
  • Najah Al-Garawi

    (Geography Department, College of Arts, Imam Abdulrahman Bin Faisal University, Dammam 34212, Saudi Arabia)

  • Muhammad Abubakar Dalhat

    (Transportation and Traffic Engineering Department, College of Engineering, Imam Abdulrahman Bin Faisal University, Dammam 31441, Saudi Arabia)

  • Omer Aga

    (Environmental Engineering Department, College of Engineering, Imam Abdulrahman Bin Faisal University, Dammam 31441, Saudi Arabia)

Abstract

Background: Recently (in 2018), females were legally allowed to drive and use automobiles in Saudi Arabia (SA) for the first time. This study investigated and analyzed the general fear of driving (GFDS), perceived self-confidence (PSCR), socio-economic variables, demographic distribution, and self-reported RTCs in novice female drivers from SA. Methods: The work was based on survey responses from 9608 participants from the first generation of female drivers from SA. Factor analysis was used to extract GFDS and PSCR scales. Results: Cronbach’s α values of 0.781 and 0.800 were observed for GFDS and PSCR, respectively. Logistic regression was employed to model road traffic collisions (RTCs) as a function of all significant variables. The results showed that of the 17.4% of geographically distributed respondents who reported RTCs, only 4% reported severe or minor injuries, and the rest (96.0%) of the accidents involved property damage. The GFDS and PSCR values showed a positive association with the RTCs of novice female drivers. Furthermore, age was not a significant influencing factor in the RTCs of novice female drivers. However, exposure factors were positively associated with the risk of RTC involvement. Conclusions: Female novice drivers who were single, divorced/widowed, employed, and had higher individual incomes were at higher risk of getting into RTCs. The female drivers who hired personal trainers, compared to those who did not, exhibited similar chances of getting involved in RTCs. An extra on-road in-traffic driving lesson is suggested to be included in the new-driver license training program for drivers with higher GFDS in SA.

Suggested Citation

  • Najah Al-Garawi & Muhammad Abubakar Dalhat & Omer Aga, 2021. "Assessing the Road Traffic Crashes among Novice Female Drivers in Saudi Arabia," Sustainability, MDPI, vol. 13(15), pages 1-11, August.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:15:p:8613-:d:606918
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    Citations

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    Cited by:

    1. Shuaiming Chen & Haipeng Shao & Ximing Ji, 2021. "Insights into Factors Affecting Traffic Accident Severity of Novice and Experienced Drivers: A Machine Learning Approach," IJERPH, MDPI, vol. 18(23), pages 1-20, December.
    2. Najah Al-Garawi & Ismail Anil, 2021. "Geographical Distribution and Modeling of the Impact of Women Driving Cars on the Sustainable Development of Saudi Arabia," Sustainability, MDPI, vol. 13(17), pages 1-19, September.
    3. Marjana Čubranić-Dobrodolac & Stefan Jovčić & Sara Bošković & Darko Babić, 2023. "A Decision-Making Model for Professional Drivers Selection: A Hybridized Fuzzy–AROMAN–Fuller Approach," Mathematics, MDPI, vol. 11(13), pages 1-24, June.
    4. Afaq Khattak & Hamad Almujibah & Ahmed Elamary & Caroline Mongina Matara, 2022. "Interpretable Dynamic Ensemble Selection Approach for the Prediction of Road Traffic Injury Severity: A Case Study of Pakistan’s National Highway N-5," Sustainability, MDPI, vol. 14(19), pages 1-18, September.

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