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Examining the Link between Road Accident Casualty and Road Width, Speed Violation, and Average Visibility Leveraging TOMS
Abstract
Road traffic accidents continue to be a significant public health concern, necessitating thorough investigation of factors contributing to casualties. This research aimed to examine the relationship between three road factors (RoadWidth, SPV, and visibility) and the number of casualties using a linear regression analysis. The study utilized the TOMS software and the lm() function in R, with data stored in the df dataframe. The results indicated that visibility and RoadWidth were not statistically significant predictors of casualties. However, the variable SPV (Speed of Vehicles) exhibited a significant relationship with the number of casualties. The model's goodness of fit was evaluated using the R-squared value, indicating that approximately 32.46% of the variation in casualties could be explained by the predictor variables. The findings underscore the importance of considering other potential factors influencing casualties, as the overall model fit was not statistically significant. Further research is recommended to explore additional variables, increase the sample size, and employ alternative modeling techniques for a comprehensive understanding of the relationship between road factors and casualties, ultimately contributing to the improvement of road safety strategies.
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