Citation

Sohaee N, Bohluli S. Safety (Basel) 2024; 10(1): e11.

Copyright

(Copyright © 2024, MDPI: Multidisciplinary Digital Publishing Institute)

DOI

10.3390/safety10010011

PMID

unavailable

Abstract

This study explores the complex connections among various socioeconomic, demographic, and technological aspects and their impact on fatal traffic accidents. Utilizing the Lasso polynomial regression model, this study explores the impact of demographic variables, including income, education, unemployment rates, and family size. Additionally, socioeconomic factors such as Gross Domestic Product (GDP) per capita, inflation rate, minimum wage, and government spending on transportation and infrastructure are examined for their impact on the occurrence of fatal accidents. This study also investigates the influence of technological advances in vehicles on the outcomes of traffic safety. The findings of this research reveal that certain factors, such as average, alcohol consumption, unemployment rate, minimum wage, and vehicle miles traveled (VMT), among others, have a substantial impact on the multifactorial model and play a considerable role in the frequency of fatal accident rates. The research results have significant implications for policymakers, highlighting the need for a comprehensive approach that accounts for the interdependence of economic indicators, behavioral patterns, and traffic safety outcomes. This study underscores the importance of considering a wide range of socioeconomic, demographic, and technological factors to develop effective policies and strategies to reduce fatal traffic accidents.

Language: en

Keywords

automation; fatal accidents; Lasso; polynomial regression; socioeconomic