###### Abstract
During the operational phase of engineering projects, highway tunnels are more susceptible to accidents and have greater risks compared to underground engineering projects such as metro and railway tunnels. This is due to the influence of external environmental factors and higher levels of uncertainty. In 1999, significant fires occurred in the Mont Blanc Tunnel in Italy and the Tauern Tunnel in Austria, resulting in devastating losses. Subsequently, European countries developed the EuroTAP program, with the German ADAC and British AA organizations as operational centers, and established the EuroTest institution to conduct an assessment and evaluation of the risk situation of existing highway tunnels in Europe. In this context, the European Commission initiated Directive 2004/54/EC, and EU member states, considering their characteristics, issued risk analysis methods applicable to their specific contexts, as shown in Table 1[3]. Outside of Europe and the Americas, countries such as Singapore have adopted the Quantitative Risk Assessment of Freeway Tunnels (QRAFT) model for their unique highway tunnels. This model enables the identification of potential hazards and provides an analysis of the probability of occurrence and potential consequences associated with these hazards [4]. \begin{table}
\begin{tabular}{c c} \hline \hline
**Country** & **Risk Analysis Methods** \\ \hline \multirow{2}{*}{France} & Based on specific disaster scenarios, quantitative models are established for risk analysis. \\ \hline \multirow{2}{*}{Norway} & A model is established to calculate the likelihood (accident frequency) of traffic accidents occurring at different locations within the tunnel. \\ \hline \multirow{2}{*}{Netherlands} & By conducting an optimized analysis of the entire accident process, the vulnerable areas of the tunnel system are identified. \\ \hline \multirow{2}{*}{Britain} & By employing the evaluation scale of “risk priority number”, the likelihood and consequences of accidents are assessed and evaluated. \\ \hline \multirow{2}{*}{Italy} & The expected probability of design accidents and the simulated consequences are calculated to determine tunnel risks. \\ \cline{2-3}  & \multicolumn{1}{c}{} \\ \end{tabular}
\end{table} 
Table 1: Risk analysis methods for EU member states. Due to concerns about tunnel operational safety, numerous scholars have conducted research on tunnel risk management using various methods. [PERSON] et al. [5; 6] performed regression analysis on historical accident data from highway tunnels over a certain period to investigate accident characteristics and the inherent relationships between these characteristics and various influencing factors related to tunnel infrastructure and the driving environment. The goal was to identify proactive improvements in tunnel infrastructure and traffic conditions to suppress the occurrence of traffic accidents. Meanwhile, numerous scholars have proposed several accident prediction models through the analysis and simulation of accidents. For instance, [PERSON] et al. [7] analyzed the annual effects of severe accidents using a random-effects logistic regression model and a negative binomial regression model and developed a collision prediction model for highway tunnels. [PERSON] [8] utilized Fire Dynamics Simulator (FDS) fire simulation software to replicate tunnel fires and employed the Real-coded Cellular Automata (RCA) method to simulate the evacuation process. The study investigated the impact of tunnel wind speed and the number of evacuees on evacuation time. [PERSON] [9] proposed an enhanced evacuation simulation model for quantitative risk assessment of highway tunnel fires. This model aims to improve the efficiency of quantitative risk assessment by estimating the potential losses of trapped individuals inside the tunnel. [PERSON] [10] based their study on traffic accident data from Pennsylvania between 1997 and 2020 to identify the characteristics and trends of road closure duration resulting from tunnel traffic accidents.