## 3 Road Operational Resilience Evolution Based on DBN
### Construction of the DBN Structure for Resilience Evolution  
First, according to the hierarchical framework of road operational resilience elements, an initial hierarchical Bayesian network structure is established, as shown in Figure 3. The nodes in the input layer correspond to the element hierarchy of the framework, specifically including nodes for specific elements of people, vehicles, roads, and environment (such as E1-1, E1-2, and E1-3). This hierarchical node type is an element type. The nodes in the middle layer correspond to the framework's factor and dimension levels, so this layer's node type is divided into factor and dimension types. Factor-type nodes include F1, F2, and F3 nodes. Dimension-type nodes include the pressure resilience nodes, the state resilience nodes, and the response resilience nodes. The nodes in the output layer correspond to the resilience level of the framework, and the RESILIENCE node represents the final road's operational resilience. Then, the static relationship between each layer node is established according to the element attribution relationship of the element hierarchical framework. The RESILIENCE node connects to the middle layer's pressure resilience node, state resilience node, and response resilience node. The pressure resilience node connects to the exposure to pressure node (F1), the pressure diversity node (F2), the uncertainty of pressure node (F3), and the pressure hazard (F4) node in factor-type nodes. The pressure hazard node connects to the hazardous to the vehicle involved (E4-1) node related to the input layer, the hazardous to casualties node (E4-2), and the hazardous to facilities node (E4-3). Similarly, the state resilience and response resilience nodes are constructed with corresponding middle layer factor-type nodes and input layer element-type nodes' associations. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Data of Elements**} & **Emergency** & **Emergency** & **Emergency** & **Emergency** & **—** \\  & **Event 1** & **Event 2** & **Event 3** & **Event 4** & **—** \\ \hline Weather conditions & 0 & 0 & 1 & 1 &... \\ Road type of accident occurrence & 0 & 1 & 0 & 1 &... \\ Traffic flow & 1 & 1 & 1 & 1 &... \\ Accident type & 1 & 1 & 1 & 1 &... \\ Vehicle types & 0 & 0 & 0 & 0 &... \\ Scattered objects situation & 0 & 0 & 0 & 0 &... \\ Fire situation & 0 & 0 & 0 & 0 &... \\ Facility losses & 0 & 0 & 0 & 0 &... \\ Number of vehicles involved & 1 & 0 & 1 & 1 &... \\ Casualty numbers & 0 & 0 & 0 & 0 &... \\ Road width & 0 & 1 & 0 & 0 &... \\ Road maintenance situation & 0 & 0 & 0 & 0 &... \\ Pavament performance & 0 & 0 & 1 & 0 &... \\ Accessible lanes & 0 & 1 & 0 & 0 &... \\ Facility functions & 0 & 1 & 0 & 0 &... \\ Road network connectivity & 0 & 0 & 1 & 1 &... \\ Design traffic capacity & 0 & 1 & 0 & 0 &... \\ Accident discovery time & 0 & 0 & 0 & 0 &... \\ Response arrival time & 0 & 1 & 0 & 0 &... \\ Disposal time & 0 & 1 & 0 & 0 &... \\ Rescue resources & 0 & 0 & 0 & 0 &... \\ Traction resources & 0 & 1 & 0 & 0 &... \\ Firefighting resources & 0 & 0 & 0 & 0 &... \\ Responsive learnability and review capacity & 0 & 0 & 0 & 0 &... \\ \hline \hline \end{tabular}
\end{table} 
Table 3: The data on emergency events after processing. To portray the dynamic characteristics of resilience under the evolution of road operation scenarios, in this paper we first analyze whether network nodes have time-varying features (i.e., whether the values of variables corresponding to nodes change significantly over time). Based on domain knowledge and data obtained from scenarios, network nodes are divided into static nodes and dynamic nodes. For example, road width robustness (E5-1) is a static node that does not change with time. In contrast, lane traffic robustness (E5-4) changes with emergency events and on-site disposal and is a dynamic node. RESLIENCE nodes in the output layer, dimension nodes in the middle layer, and some factor nodes are all affected by input layer elements with time-varying features that are associated with them.