A generalized ordered logit analysis of risk factors associated with driver injury severity

Aidoo, Eric Nimako; Ackaah, Williams

doi:10.1007/s10389-019-01135-8

Cited by 5 publications

(1 citation statement)

References 35 publications

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“…However, the disordered response model fails to reflect the internal order of the accident severity variable, and scholars use the ordered response model instead [ 16 , 17 ]. In addition, the generalized ordered model [ 18 , 19 , 20 ] and random parameter model [ 21 , 22 ] are also introduced. The generalized ordered model is an improvement of the ordered model; it believes that the external variables have different effects on different alternatives, while the random parameter model believes that the parameters in the model are random.…”

Section: Literature Reviewmentioning

confidence: 99%

Insights into Factors Affecting Traffic Accident Severity of Novice and Experienced Drivers: A Machine Learning Approach

Chen

Shao

2021

IJERPH

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Traffic accidents have significant financial and social impacts. Reducing the losses caused by traffic accidents has always been one of the most important issues. This paper presents an effort to investigate the factors affecting the accident severity of drivers with different driving experience. Special focus was placed on the combined effect of driving experience and age. Based on our dataset (traffic accidents that occurred between 2005 and 2021 in Shaanxi, China), CatBoost model was applied to deal with categorical feature, and SHAP (Shapley Additive exPlanations) model was used to interpret the output. Results show that accident cause, age, visibility, light condition, season, road alignment, and terrain are the key factors affecting accident severity for both novice and experienced drivers. Age has the opposite impact on fatal accident for novice and experienced drivers. Novice drivers younger than 30 or older than 55 are prone to suffer fatal accident, but for experienced drivers, the risk of fatal accident decreases when they are young and increases when they are old. These findings fill the research gap of the combined effect of driving experience and age on accident severity. Meanwhile, it can provide useful insights for practitioners to improve traffic safety for novice and experienced drivers.

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