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Journal Article

Citation

Omar Mohamed B, Yusoff NI, Mubaraki M, Rosyidi SA. Open Transp. J. 2019; 13(1): 154-161.

Copyright

(Copyright © 2019, Bentham Science Publishers)

DOI

10.2174/1874447801913010154

PMID

unavailable

Abstract

BACKGROUND:

Globally, Road Traffic Accidents (RTAs) are one of the significant causes of fatality and injury. In Libya, RTAs have resulted in disabilities and were the third leading cause of death. However, there is a lack of information on RTAs and road safety in Libya.

Objective:

The present study aims to fill the knowledge gap by performing a statistical analysis to identify the factors associated with road accident severity in El-Brega Coastal Freeway.

Methods:

RTAs data extracted from police investigation reports in Ajdabiya Municipality for the period from 2001 to 2010. Then descriptive analysis and Binary logistic regression model (BLM) are applied to analyzing the data.

Results:

Descriptive analysis results showed that between 2001 and 2010, approximately 45% of RTAs in Ajdabiya Municipality occurred on El-Brega Coastal Freeway, and more than 1225 individuals lost their lives or sustained injuries in these RTAs. Furthermore, Sixty-two percent (n = 137) of those who died in accidents were from the 20-45 age group. BLM Results concluded that only eight predictors have statistical significant with accident injury severity. Five of them increase the likelihood of injury severity. A head-on collision is the prime influence factor to increase injury severity odds, followed by high-speed driving, Weekends, horizontal curves, and driver's age. While accident injury tends to be less severe with the other predictors like rollover collision, rear-end collision, and accidents involving animals.

Conclusion:

Thus, implementing the use of seat-belt and speed control regulations, with activating ambulance services are the urgent countermeasures to enhance road safety.
Keywords: Coastal freeway, Descriptive analysis, El-Brega Road, Libya, Traffic accident severity, BLM.


Language: en

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