Ordinal regression analysis of traffic collision accidents in Jordan 2021: factors and severity assessment

Author:

Darwish Walaa,Darwish Haneen

Abstract

One of the significant challenges that the world is confronting is road traffic accidents. The aim of this study is to determine the key factors contributing to traffic collision accidents and to utilize an ordinal regression model to identify the factors that contribute to accident severity. This will be achieved by fitting a suitable equation based on a dataset obtained from the Traffic Institute's database for the year 2021. The findings from the ordinal logistic regression analyses indicate that weather conditions, road surface, speed limit and illumination levels are significant factors that contribute to the severity of crashes with p-values of 0.003, 0.085, 0.025 and .002 respectively. Hour of the day, day of the week, week and governorate are insignificant in collision accidents in Jordan in 2021. In this comprehensive study on traffic collision accidents in Jordan during 2021, our analysis has revealed some significant findings. Our data indicates that the peak period for traffic collision accidents was between 18:00 to 18:59, and Thursday was found to have the highest number of incidents. In terms of the month, July recorded the highest number of accidents. It was also noted that Amman had the largest share of accidents. These findings highlight the need for increased awareness and stricter enforcement of traffic regulations during peak periods and in high-risk areas.

Publisher

4S go, s.r.o.

Subject

Industrial and Manufacturing Engineering,Transportation,Civil and Structural Engineering,Business and International Management

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