Indexing Crash Worthiness, Crash Aggressivity, and Total Secondary Safety for Major Car Brands: A Case Study of Iran
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A growing body of research is being conducted all over the world to evaluate and compare the safety impacts of different car brands. This issue has also received a considerable attention among the safety experts in Iran, where the number of road fatalities is around 16,500 lives per year. This study aims at indexing crash worthiness, crash aggressivity, and total secondary safety of the 20 most prevalently used passenger car brands of Iranian fleet. For this purpose, the data pertaining to 167,759 crashes and 335,518 drivers involved in those crashes that occurred in Iran from 2009 to 2012 were used. Binomial logistic regression model was applied to define the above-mentioned indices based on driver’s injury severity level. The results showed that most of the domestic brands have a poorer performance than the foreign ones in all three indices. Furthermore, it was revealed that Kia and Suzuki have a better performance and Sepand and Pride have a poorer performance compared to the other brands. Our findings might also be integrated with the findings of other similar studies around the world. This could be helpful for car manufacturers both in Iran and across the world to benchmark the best performing car brand in vehicle safety domain and improve the designing of their own car brands.
KeywordsCrash worthiness Crash aggressivity Total secondary safety Car brand Iran Driver’s injury severity
The authors gratefully thank Mohammad Mehdi Besharati and Hasan Mohamdzadeh for their valuable comments and useful assistances on this study.
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- 3.Stigson H, Ydenius A, Kullgren A (2006) Variation of crash severity and injury risk depending on collisions with different vehicle types and objects. In: 2006 international IRCOBI conference on the biomechanics of impact, Madrid, Spain, 20–22 SeptemberGoogle Scholar
- 4.Newstead S, Watson L, Cameron M (2007) An index for rating the total secondary safety of vehicles from real world crash data. 51st annual proceedings, Association for the Advancement of Automotive MedicineGoogle Scholar
- 13.Gujarati D (2014) Econometrics by example. Palgrave Macmillan, BasingstokeGoogle Scholar
- 14.Gail M, Krickeberg K, Samet J, Tsiatis A, Wong W (2007) Statistics for biology and health. Springer, BerlinGoogle Scholar
- 15.Lund ALM (2016) Binomial logistic regression using spss. https://statistics.laerd.com/spss-tutorials/binomial-logistic-regression-using-spss-statistics.php. Accessed 26 Oct 2106
- 19.Kashani AT, Rabieyan R, Besharati MM (2016) Modeling the effect of operator and passenger characteristics on the fatality risk of motorcycle crashes. J Inj Violence Res 8(1):35Google Scholar