Exploring the injury severity of unlicensed powered two- and three-wheeler drivers in two-vehicle crashes in China

Abstract Large presence of unlicensed powered two- and three-wheeler (PTW) drivers in China pose a significant threat to road safety. In this study, a customized Deep Forest Model (DF-ptw) is constructed to investigate the effect of unlicensed PTW drivers on crash severity in two-vehicle crashes, using a recent 3-year historical crash data. SHapley Additive explanation (SHAP) and Partial Dependence Plot (PDP) analysis reveal that unlicensed motorcyclists are significantly more likely to suffer serious injuries in two-vehicle crashes compared to unlicensed auto-rickshaw drivers. Additionally, factors such as drunk driving, fatigued driving, and being an unlicensed driver over the age of 53 notably elevate the risk of serious injury or death, with unlicensed motorcyclists being disproportionately affected. Moreover, self-employed unlicensed PTW drivers face a higher probability of serious injury or fatality in crashes compared to farmers, blue-collar, and white-collar workers. Unlicensed PTW drivers are also more susceptible to severe or fatal injuries on national and provincial roads, in low visibility conditions, during late-night hours, on non-separated roads, and at dusk or dawn. Based on these findings, this study proposes to reduce the frequency and severity of crashes involving unlicensed PTW drivers by focusing on more stringent eligibility checks, increasing safety awareness, and implementing advanced safety measures.