# Factors Affecting Rear-End Collisions in Underground Road Junctions Using VISSIM
## 3 Methodology
### Simulation Network and Scenario  
Because there are currently no existing three-dimensional intersections in operational underground roads in Republic of Korea, a virtual simulation network was constructed. The simulation network was set up according to the Highway Capacity Manual [32], Explanation of the Rules for Structural and Facility Standards for Roads [33], and Design Guidelines for Underground Roads in Urban Areas [34], which are the Korean design guidelines. The network consisted of a diamond-shaped underground-underground junction with a main line of 10 km and connections of 1 km.  
Figure 1: Research framework.  
Underground roads and the surrounding areas, including ramp, diverge areas, and merge areas, were selected as the studied area. Figure 2 shows the simulation network used in the study and the scope of the studied area where the data were analyzed. Table 1 describes the simulation network components.  
Table 2 describes the simulation scenarios set up for the analysis. The simulation was conducted by dividing the analysis into cases with and without driving speed distribution in the underground road. To collect individual vehicle information through the simulation, we set up scenarios according to the mainline traffic volume and the rate of vehicles entering the connecting road. In the case of the mainline R1 and R2 in Figure 2, the traffic volume varied from 1600 pcph (LOS B) to 4000 pcph (LOS E) depending on the level of service, and in the case of the connecting ramp, the percentage of vehicles entering the connecting ramp from the mainline varied from 15% to 40% in 5% increments. Each scenario was simulated 30 times, and 1 h of individual vehicle driving data (not including the first 600 s as a warm-up period) was used for analysis.  
\begin{table}
\begin{tabular}{c c} \hline
**Component** & **Content** \\ \hline Lane & Main road: 2 lanes one way \\  & Connection road: 1 lane \\ \hline Vehicle composition & Underground road: Car only \\  & Ground road: All vehicle \\ \hline Link Length & Main road: 10 km \\  & Connection road: 1 km \\ \hline Designed speed & Main road: 80 km/h \\  & Connection road: 60 km/h \\ \hline Gradient of link & Main road: 8\% \\  & Connection road: 10\% \\ \hline Lane width & Main road: 3.5 m \\  & Connection road: 3.5 m \\ \hline Capacity & Main road: 4000 pcph (veh/hour) 1 \\  & Connection road: 1800 pcph (veh/hour) 1 \\ \hline Acceleration and deceleration lane & Acceleration: 205 m \\  & Deceleration: 180 m \\ \hline Separation distance between JC & Main road: 2 km \\ \hline Curve radius & Main road: 450 m \\  & Connection road: 250 m \\ \hline \end{tabular}
\end{table}
Table 1: Description of the simulation network.  
Figure 2: Simulation network (left: design of network, Right: Analysis Section of Network).  
To construct the speed distribution, we used data from the Shinwol-Yeoui underground road in Seoul. Figure 3 shows the Shinwol-Yeoeui underground road in Seoul. The Shinwol-Yeoui underground road is a 7.53 km long road that connects Shinwol-dong, Yangcheon-gu district to Yeouido-dong, Yeongdeungpo-gu district. The road has a speed limit of 80 km/h from the Shinwol direction to Yeoui JCT and 60 km/h after Yeoui JCT. There are also two off-ramps from Yeoui JCT to Yeoui-daero and Olympic-daero, and the off-ramp to Olympic-daero is a single lane, which is similar to the simulation network in this study.  
VDS (vehicle detection system) data collected for two months from 1 September 2021 to 31 October 2021 were used. Figure 4 shows the speed distribution set up for the underground road environment. Based on the average hourly section speed and traffic volume, we created speed distributions for the main line, diverging area, and road connection and applied them to VISSIM.