Evaluation of effects of risk factors on injury severity of single-vehicle accidents

Approximately 30% of total road traffic accidents in India are single-vehicle accidents (SVAs). The main objective of the present study is to evaluate the individual and interacted effects of risk factors on SVA severity. Using 10-year (2011–2020) accident data reported from Itanagar and Shillong, India, two sets of binary logistic regression models (model-without-interaction and model-with-interaction) were developed. The present study considered two-way and three-way interaction analysis in the model-with-interaction. Modelling results show that in the model-without-interaction, seven categorical variables (18–24 age group, 25–40 age group, above 40 age group, heavy motor vehicle, 6 p.m.–12 a.m., rushed driving, and rollover) in the Itanagar study area and four categorical variables (female, light motor vehicle, out-of-control, and run-off-road) in Shillong study area were shown statistically significant for the SVA severity. For the model-with-interaction, there were 12 significant interactions (seven two-way interactions and five three-way interactions) in the Itanagar study area and seven significant interactions (five two-way interactions and two three-way interactions) in the Shillong study area. These findings will be useful for transportation policymakers while implementing correctives to improve road safety in these regions.