![]() ![]() Considering the prevalence and hazards of truck overloading, it is of great practical significance to conduct appropriate research and analysis on overloaded trucks to improve road safety. Truck overloading is also associated with other negative phenomena, including the disorder of the road transport market and an increase in maintenance costs for hardware infrastructure. In addition, compared with properly loaded vehicles, overloaded trucks are far more likely to damage road traffic infrastructure, as manifested in shortening the service life of the road pavement, increasing the fatigue damage of the bridge, and even causing the bridge to collapse. According to statistics, more than 80% of truck-related crashes result from truck overloading. Undeniably, overloaded transportation does help enterprises improve their transportation efficiency and reduce operating costs, but at the same time, it may also pose serious potential risks to road safety, and can even lead to severe accidents. This phenomenon is quite common in middle-income countries, where the demand for cargos transportation is relatively considerable. In a narrow sense, truck overloading is the act of loading a commercial truck with more cargo than the vehicle’s rating. As we all know, there are a number of factors that can contribute to road traffic accidents, among which the inappropriate transportation behavior of commercial trucks, especially truck overloading, is one of the main causes. Although the industry management departments in various countries have taken proper measures, and meanwhile achieved certain results, the annual number of road traffic deaths remains unacceptably high, reaching 1.35 million in 2016. Over the years, road safety issues have attracted great attention from all walks of life. Our findings are useful for industry-related departments in formulating and implementing corresponding countermeasures, such as strengthening the inspection of commercial trucks, increasing the penalties for overloaded trucks, and installing certain protective equipment and facilities on crash-prone sections. In regards to the fixed variables, it is likely that the single curve, rollover, autumn, and winter variables will increase the probability of fatalities, whereas the provincial highway, country road, urban road, cement, wet, and head-on variables will decrease the likelihood of death. In the best-performing model, a total of fifteen variables are found to be significant at the 99% confidence level, including random variables such as freeway, broadside hitting, impaired braking performance, spring, and evening. For in-depth analysis, three models are developed, including a binary logit model, a random parameter logit model, and a classification and regression tree, but the results show that the random parameter logit model outperforms the other two. This is the first time that the injury severity has been studied from the perspective of crashes involving overloaded trucks, and meanwhile in a scenario of mountainous highways. Given the complexity and variability of mountainous highways, this study examines 1862 overloaded-truck-related crashes that happened in Yunnan Province, China, and attempts to analyze the key factors contributing to the injury severity. ![]() Nevertheless, several negative consequences are associated with this illegal activity, including road subsidence, bridge collapse, and serious casualties caused by accidents. Overloaded transport can certainly improve transportation efficiency and reduce operating costs. ![]()
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