# Analysis of Macroscopic Traffic Network Impacted by Structural Damage to Bridges from Earthquakes
## 5 Conclusions  
Highway systems play a key role in providing mobility to society, especially during emergency situations including earthquakes. Bridges in highway systems are susceptible to damage from earthquakes, causing traffic capacity loss leading to a serious impact in surrounding areas. To better prepare for such scenarios, it is important to estimate capacity loss and traffic disruptions from earthquakes. For this purpose, a traffic capacity analysis-based methodology is developed to model the performance of a transportation network immediately following an earthquake using a macroscopic multi-level urban traffic planning simulation model EEMME4. The proposed method employs the second order linear approximation (SOLA) traffic assignment and calculates total system travel time for various capacity loss scenarios due to bridge damage from earthquakes. The proposed methodology is applied to Pohang City in Korea to evaluate the performance of traffic network for various scenarios. As expected, travel time increases and travel speed decreases significantly as the intensity of earthquake increases. However, similar correlation is not found in traffic volume. It seems that traffic volume of bridges varies depending on the location of the bridge. It is believed that changes in traffic routing at different levels of earthquake scenarios lead to different traffic volume outputs. Based on the traffic volume comparison, there was significant diversion on Bridges 2 and 4 from Bridge 1. Additionally, fewer vehicles have taken Bridges 5 or 6. It is believed that vehicles that used Bridges 5 or 7 might have taken alternative routes to minimize their travel times. From the results, it was readily seen that Bridges 2 and 4 would play a significant role when the functionality of other bridges was impacted by an earthquake. The results are expected to help estimate the impacts on transportation network when earthquakes bring traffic capacity loss on bridges. In this study, the same origin and destination table was utilized for all scenarios. However, travel patterns and behaviors differ greatly in events of natural disasters, including earthquakes. While it is almost impossible to predict this exact travel pattern, it might be advantageous to develop a framework enabling exploration of potential scenarios where travel behaviors are significantly altered due to earthquakes. The outcome of this study should help one analyze the traffic network impact caused by structural damage to bridges due to earthquakes. [PERSON] and [PERSON]-[PERSON] conceived of the presented idea. [PERSON] developed the theory and performed the computations. [PERSON] and [PERSON] revised the manuscript. All authors have read and agreed to the published version of the manuscript. This work was partially supported by NRF-2020R1A2C1011060 of the Korean government and a grant (21 SCIP-B146959-04) from Construction technology research program funded by Ministry of Land, Infrastructure and Transport of Korean government. **Institutional Review Board Statement:** Not applicable. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & **No.1** & **No.2** & **No.3** & **No.4** & **No.5** & **No.6** & **No.7** \\  & **Bridge** & **Bridge** & **Bridge** & **Bridge** & **Bridge** & **Bridge** \\ \hline
**Minor Damage** & \(1\%\) & \(7\%\) & \(-1\%\) & \(-7\%\) & \(-11\%\) & \(-28\%\) & \(-6\%\) \\ \hline
**Moderate Damage** & \(-10\%\) & \(17\%\) & \(-3\%\) & \(-2\%\) & \(-23\%\) & \(-43\%\) & \(-43\%\) \\ \hline
**Major Damage** & \(-12\%\) & \(66\%\) & \(13\%\) & \(30\%\) & \(-2\%\) & \(-71\%\) & \(-71\%\) \\ \hline \hline \end{tabular}
\end{table} 
Table 10: Traffic volume comparison. **Informed Consent Statement:** Not applicable. **Data Availability Statement:** Data available on request. **Acknowledgments:** This work was supported by NRF-2020R1A2C1011060 of the Korean government and a grant (21 SCIP-B146959-04) from Construction technology research program funded by Ministry of Land, Infrastructure and Transport of Korean government.