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Modeling the Impact of Weather Conditions on Pedestrian Injury Counts Using LASSO-Based Poisson Model

  • Research Article-Civil Engineering
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Abstract

Statistical models for measuring the impact of adverse weather conditions on pedestrian injuries are of great importance for enhancing road safety measures. The development of these models in the presence of high collinearity among the weather conditions poses a real challenge in practice. The collinearity among these conditions may result in underestimation of the regression coefficients of the regression model, and hence inconsistency regarding the impact of the weather conditions on the pedestrian injuries counts. This paper presents a methodology through which the penalization-based regression is applied to model the impact of weather conditions on pedestrian injury in the presence of a high level of collinearity among these conditions. More specifically, the methodology integrates both the least absolute shrinkage squared operator (Lasso) with the cross-validation approach. The statistical performance of the proposed methodology is assessed through an analytical comparison involving the standard Poisson regression, Poisson generalized linear model (Poisson-GzLM), and Ridge penalized regression model. The mean squared error (MSE) was used as a criterion of comparison. In terms of the MSE, the Lasso-based Poisson generalized linear model (Lasso-GzLM) revealed an advantage over the other regression models. Moreover, the study revealed that weather conditions involved in this study are of insignificant impact on pedestrian injury counts.

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Authors and Affiliations

  1. Department of Mechanical and Industrial Engineering, Qatar University, P.O. Box 2713, Doha, Qatar

    Galal M. Abdella

  2. Department of Engineering, Utah Valley University, 800 W University Pkwy, Orem, UT, USA

    Khaled Shaaban

  3. Department of Civil Engineering, Qatar University, P.O. Box 2713, Doha, Qatar

    Khaled Shaaban

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  1. Galal M. Abdella
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  2. Khaled Shaaban
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Correspondence to Khaled Shaaban.

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Abdella, G.M., Shaaban, K. Modeling the Impact of Weather Conditions on Pedestrian Injury Counts Using LASSO-Based Poisson Model. Arab J Sci Eng 46, 4719–4730 (2021). https://doi.org/10.1007/s13369-020-05045-w

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  • DOI: https://doi.org/10.1007/s13369-020-05045-w

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