# Urban Expressway Renewal Strategy Based on Knowledge Graphs
## 6 Experimental Analysis of Road Renewal Decision-Making  
### Results of Expressway Based on Knowledge Graph  
In this paper, we used owlready2 and RDFlib to batch-fill the expressway instances, pavement functional condition instances, road damage instances, and damage treatment instances into the urban road renewal ontology, to provide data support for expressway renewal decisions. Combined with the scenario of expressway renewal in this paper, the designed expressway instance data are shown in Table 10.  
Table 10 shows example data of expressways designed according to the two road maintenance standards, which contain the main attributes used to evaluate roads. Since many metropolitan cities treat expressways as Class I roads, this paper also sets the road class of expressways as Class I roads, and corresponds the expressway renewal requirements to the requirements in the standards for Class I roads. Based on the example data of the expressway in Table 10 and the knowledge reasoning rules, the knowledge inference based on the knowledge graph matches the expressway to the corresponding renewal solutions (Figure 7). \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**ID** & **hasCondition** & **trafficLoad** & **PCI** & **RDI** & **RQI** & **SRI** \\ \hline EW01 & skid resistance loss & extremely severe & 80 & 85 & 89 & 80 \\ EW02 & pavement seepage & extremely severe & 85 & 83 & 88 & 81 \\ EW03 & pavement wear & particularly severe & 88 & 80 & 84 & 90 \\ EW04 & asphalt ageing & particularly severe & 90 & 80 & 82 & 86 \\ EW05 & pavement irregularity & particularly severe & 89 & 82 & 80 & 85 \\ EW06 & pavement irregularity & particularly severe & 88 & 89 & 88 & 80 \\ EW07 & asphalt ageing & severe & 80 & 80 & 86 & 80 \\ EW08 & pavement seepage & moderate & 95 & 85 & 80 & 86 \\ EW09 & pavement seepage & moderate & 91 & 87 & 90 & 85 \\ EW10 & pavement seepage & moderate & 93 & 86 & 85 & 80 \\ EW11 & skid resistance loss & mild & 90 & 88 & 80 & 86 \\ EW12 & asphalt ageing & mild & 90 & 80 & 87 & 85 \\ EW13 & asphalt ageing & mild & 80 & 78 & 85 & 83 \\ EW14 & pavement seepage & extremely severe & 80 & 79 & 85 & 76 \\ \hline \hline \end{tabular}
\end{table} 
Table 10: Examples of urban expressways. In the example in Figure 7, the relationships in the boxes are the results were obtained by inference. The inference machine first matched the potential risk of the road (e.g., cracking, loosening, and block cracking) based on the functional condition of the pavement (_hasCondition_) of the expressway EW12 and the causes of road damages by rule R1, which provides a reference for the preventive maintenance of the expressway. Properties such as road surface functional condition, traffic load, and PCI provided the basis for matching the renewal solution of the expressway, and based on these properties, the reasoner matched the one of the four corresponding applicable renewal solutions for EW12 with the help of rule set R2. The inspection of the reasoning results of the expressway renewal revealed that there is one example (EW14) that failed to match the renewal solution; therefore, based on the decision-making process in Figure 4, a further case similarity-based auxiliary decision strategy was required. Based on the attribute vector similarity, Algorithm 2 matched the expressway EW02 with the most similar road condition to EW14, and matched the renewal solution corresponding to EW02 for EW14 (Figure 8). Figure 8: Results based on knowledge reasoning and case similarity. Figure 7: Result of expressway renewal based on the knowledge graph. In Figure 8, as the expressway EW14 failed to obtain the renewal solution through knowledge inference, Algorithm 2 matched five applicable solutions for EW14 based on the attributes of pavement functional condition, traffic load, PCI, RDI, RQI, SRI, and cosine similarity, and achieved the intelligent decision of expressway renewal. This result shows that combining case similarity with knowledge inference can provide more comprehensive support for expressway updating decision-making.