# Analysis of the Severity of Heavy Truck Traffic Accidents Under Different Road Conditions
## 1 Introduction  
In China, road freight transport accounts for 72.4% of the total freight transport, with heavy truck transport playing a pivotal role and having a significant impact on the national economy and social development [1, 2]. Although heavy trucks play an irreplaceable role in road transport, their large size, heavy load, easy rollover, and braking difficulties make them more likely to cause traffic accidents, especially those resulting in mass casualties [3]. In recent years, the number of serious traffic accidents involving heavy trucks has been steadily increasing, causing significant loss of life and property [4]. In addition to China, heavy truck accidents have caused significant losses and fatalities worldwide. In South Korea, truck-related accidents made up 13% of all traffic accidents, and the proportion of fatalities caused by truck traffic accidents was 24% in 2019 [5]. In Europe, heavy trucks are involved in 4.5% of police-reported traffic incidents and 14.2% of fatal traffic accidents [6]. In Australia, despite comprising only about 3% of registered vehicles, heavy trucks account for 18% of all road fatalities [7]. In the United States, the number of fatal truck accidents increased from 3211 in 2009 to 5788 in 2021, with each fatal injury averaging an economic cost of $1,778,000, according to the National Safety Council injury information of 2021 [8]. Thus, comprehensive research on heavy truck operational safety is essential to inform targeted preventive measures, helping traffic management departments to minimize both the frequency and severity of such accidents. Heavy truck safety research primarily addresses two aspects: driver behavior and accident analysis. Most current studies focus on the driving behavior of heavy truck drivers, including analyses of driving behavior, identification of dangerous behaviors, and assessments of driving safety risks [9]. This aspect of research primarily targets the operational processes of heavy trucks and can aid in reducing the occurrence of heavy truck traffic accidents. However, the randomness associated with accident occurrences means that it is impossible to completely avoid traffic accidents [10]. The \"Vision Zero\" initiative also suggests that the main goal of road traffic safety management should be to minimize the serious consequences of accidents, such as casualties, rather than solely preventing the occurrence of traffic accidents [11]. Research on heavy truck traffic accidents can provide a basis for reducing the severity of traffic accidents. Such studies typically rely on traffic accident data recorded by traffic management departments, which usually include the severity of accidents (such as property damage, personal injury, and fatalities), personnel information, vehicle performance, road conditions, traffic environment, and illegal behaviors [12; 13]. Currently, research on heavy truck traffic accidents primarily includes statistical analyses of accident characteristics and modeling analyses of accident severity. In terms of statistical analysis of heavy truck accident characteristics, [PERSON] [14] analyzed and summarized the characteristics of heavy truck traffic incidents based on factors such as accident form, time, load, speed, weather, and driver age. [PERSON] et al. [15] compared heavy truck traffic accident data from Zhejiang and Jilin provinces in China and found significant differences in the number, severity, causes, and complexity of accidents between the two regions. However, statistical analyses of accident characteristics can only provide a rough indication of simple patterns, which cannot directly support the formulation of traffic management measures aimed at reducing accident severity. Severity modeling typically employs accident severity as the dependent variable and factors such as personnel data, vehicle performance, road conditions, traffic environment, and violations as independent variables.