The Impact of Weather Conditions on the Number of Road Accidents in England

Authors

  • Piotr Gorzelańczyk *

    Department of Transport, Stanislaw Staszic State University of Applied Sciences in Pila, Pila 64-920, Poland
  • Dominique Trual Molintas

    PATTS College of Aeronautics, Benguet State University, Cordillera 2613, Philippines

DOI:

https://doi.org/10.55121/tdr.v3i2.875

Keywords:

Traffic Accident, Road Collision, Road Traffic Safety (RTS), Weather Conditions

Abstract

This study investigates the relationship between average monthly surface temperature and road traffic accidents in England, across ten years. Using (n = 120) on collisions, casualties, and average surface temperature, we applied descriptive statistics, Pearson and Spearman correlations, simple linear regressions, and a multivariate regression controlling for monthly seasonality. Explicitly, surface temperature is treated as a representative indicator of broader environmental influences on accident occurrence, indicative of seasonal mobility patterns. Driver behaviour, vehicle condition, and traffic management are the controllable factors; and seasonal weather conditions and surface temperature are the uncontrollable factors. A positive correlation between temperature and both the number of collisions (r = 0.288, p = 0.0014) and casualties (r = 0.343, p = 0.0001) is defined. In simple linear regression, a 1 °C increase in temperature was associated with approximately +5 collisions and +10 casualties per month. However, when controlling for seasonality through month dummy variables, the effect of temperature became statistically insignificant (β = −1.91, p = 0.764). This suggests that seasonal traffic patterns wields greater influence; rather than temperature itself. Moreover, the correlation between temperature and collisions was considerably stronger after 2020 period (r = 0.578) compared to 2014–2019 (r = 0.269), potentially reflecting alterations in mobility patterns due COVID-19 pandemic. In conclusion: Although in simple models a relationship is apparent with traffic accidents; this study finds temperature does not emerge as an independent predictor in contrary seasonality. Future research should incorporate traffic exposure, additional meteorological variables and nonlinear modelling approaches.

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