## 2 Road Traffic Situation Assessment Model
### Urban Road Monitoring Network
#### 2.1.4 Collaborative Monitoring Model of the Road Traffic Situation  
Nodes in the urban road monitoring network detect emergencies. In order to analyze the impact of such emergencies on the road traffic of the road network, a collaborative monitoring model of road traffic situation under emergencies is built, as shown in Figure 3. This model can not only identify the road traffic state, but also predict the future traffic trend of the road to a certain extent. \begin{table}
\begin{tabular}{c c} \hline \hline
**Traffic Situation Level** & **Situation Level Description** \\ \hline \multirow{3}{*}{unobstructed state} & When in an unobstructed state, vehicles are widely spaced and traffic moves in an orderly manner, without interference from road events. Traffic managers do not need to manually direct traffic on city roads, and a high level of traffic safety and efficiency can be achieved. \\ \hline \multirow{3}{*}{slightly unobstructed state} & When it is in a slightly unobstructed state relative to the unobstructed state, the number of vehicles on that city road increases, but it does not cause congestion. The traffic order is good, and if a road incident occurs, it will not cause disorder in the city road traffic. Traffic efficiency is at a high level at this time. \\ \hline \multirow{3}{*}{mild congestion} & When in mild congestion, the traffic road is sensitive to sudden disruptions and affected by emergencies. When disturbed, the road traffic is less efficient. At this time, the normal operation of traffic can be ensured with the intervention of traffic managers. \\ \hline \multirow{3}{*}{moderate congestion} & In the state of moderate congestion, the traffic road is more sensitive to the interference of emergencies and more affected by emergencies. When disturbed, road traffic is inefficient. As the complexity of urban roads increases, the chance of conflicts between vehicles increases, and most vehicles are delayed at intersections, resulting in low traffic efficiency. At this time, the traffic operation can be maintained under the intervention of the traffic manager. \\ \hline \multirow{3}{*}{severe congestion} & In the state of severe congestion, the traffic road is very sensitive to the disturbance of emergencies, and it is easy to produce great fluctuations. When disturbed, most vehicles will be greatly affected, and the road traffic efficiency is very low. Urban roads are becoming more complex. At this time, the traffic manager needs to arrange multiple traffic departments to conduct traffic dredging and maintain traffic order. \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Road traffic situation level description. In the urban road monitoring network, the event source node \(v_{i}\) monitors the target event and uploads the target event information set \(A=[a_{1},a_{2},a_{3},\ldots,a_{n}]\). In the target event information set \(A\), \(a_{1}\) is the id information of the event source node, and \(a_{2}-a_{n}\) are the monitored target event data, such as event type, target vehicle license plate, vehicle speed, driving direction, etc. The master node searches and communicates with collaborative nodes that can monitor the same target event according to the road correlation and obtains the monitoring data of each cooperative node. The monitoring data of each cooperative node is recorded as the cooperative node monitoring dataset \(D=\left\{M_{j}\mid j\in I,I=0,1,2,\ldots,N\right\}\) of the event source node. \(N\) is the number of nodes, where \(M_{0}\) represents the monitoring information of the master node, and the default is \(0\); \(M_{a}(a=1,\ldots,N)\) is the data information of the monitoring node. Assuming that node \(v_{j}\) is the road coordination node of the target event, node \(v_{j}\) will upload the monitoring data \(M_{j}=\left[m_{j},m_{j}^{1},m_{j}^{2},\ldots,m_{j}^{M}\right],\) where \(m_{j}\) is the road, after receiving the server request. The id information of the cooperative node, \(m_{j}^{1}-m_{j}^{M}\), is the monitored road data.