This study developed a fire evacuation simulation model for a six-level underground station to evaluate evacuation efficiency under both dynamic and static conditions, including structural damage, smoke propagation, and real-time crowd congestion. Two representative pathfinding algorithms, Dijkstra’s and A*, were applied to analyze evacuation performance across eight fire scenarios occurring at different locations within the station. When only static factors were considered, both algorithms yielded identical maximum evacuation times, indicating comparable performance. However, the A* algorithm exhibited a significantly shorter computation time than Dijkstra’s, demonstrating higher operational efficiency. When dynamic variables such as real-time congestion and smoke-induced visibility reduction were introduced, the maximum evacuation times varied irregularly between the two algorithms. This outcome suggests that, under dynamic fire conditions, route guidance based solely on current information rather than predictive modeling may lead to suboptimal evacuation outcomes. Therefore, this study emphasizes the importance of establishing a predictive disaster management system capable of forecasting fire and smoke propagation, as well as a centralized control system that can dynamically distribute evacuees to enhance evacuation efficiency in deep underground stations.

Herein, the Dijkstra algorithm was used to develop a model that considers evacuee congestion and derives an optimal evacuation route in underground structures in the event of an earthquake. The ground conditions and seismic intensities were varied, and the evacuation route was analyzed for four cases. The damage index for each underground structure due to an earthquake was determined considering the ground conditions and structure depth, and the evacuation speed reduction was evaluated as a function of the damage index. A congestion coefficient was applied when the evacuation capacity exceeded the threshold to reflect the evacuation speed reduction due to increased congestion in the same evacuation route. The evacuation route in some sections changed when congestion was considered, and the final evacuation time increased significantly when the congestion coefficient was applied. When the evacuation capacity at each node exceeded the threshold, the 1/3 value was applied as the congestion coefficient to evacuation velocity. When the original evacuation route was used after applying the congestion coefficient, the evacuation time increased by up to 220%. However, the evacuation time can be reduced by applying an alternative route that considers congestion. When an alternative route derived from considering congestion was used, the evacuation time decreased by up to 45% compared to that when the original route was used, and the time required decreased by up to 840 s. Hence, the reduction in evacuation speed due to evacuee congestion must be considered to derive alternative, optimal evacuation routes in the event of a disaster. In addition, evacuation routes should account for the location of evacuees using technologies such as real-time indoor positioning to consider the congestion level of evacuees.

This study investigates the seismic fragility of railway tunnels intersecting fractured geological zones using a nonlinear numerical approach. A series of dynamic analyses was performed on tunnel models subjected to multiple ground motions with varying frequency contents. The structural response was evaluated in terms of maximum bending moment, and the resulting damage indices were used to classify damage states. Based on these classifications, seismic fragility functions were developed for tunnels passing through fractured zones using a lognormal cumulative distribution with peak ground acceleration (PGA) as the intensity measure. The fragility curves indicated that the probabilities of exceeding minor, moderate, and extensive damage states surpassed 50% at PGAs of approximately 0.289 g, 0.578 g, and 0.91 g, respectively. These findings highlight the elevated seismic risk in tunnels intersecting fractured ground and emphasize the necessity of incorporating geological conditions into seismic design frameworks.

In evacuation analysis for underground stations, Dijkstra’s algorithm is widely used to estimate the maximum evacuation time on the assumption that it returns a unique and reproducible route. This assumption does not hold in structurally symmetric networks, where many routes share an identical cost and the route actually returned depends on an arbitrary, implementation-dependent tie-breaking rule. The aim of this study is to quantify how much the maximum evacuation time varies solely as a result of this tie-breaking rule, and to determine how many repeated executions are required before that variability is adequately characterized. A six-level underground station network of 720 nodes and 2222 edges was used. A random tie-breaking rule was implemented within Dijkstra’s algorithm, and the evacuation simulation was repeated under independently seeded runs of 1, 10, 25, 50, 100, and 1000 iterations while the station layout, movement speeds, congestion thresholds, and evacuee distribution were held fixed. A single execution produced a maximum evacuation time of 782 s, whereas the 1000-iteration case yielded a range of 671–864 s. The mean and median stabilized within 10–25 iterations, but the observed minimum and maximum continued to widen through 1000 iterations. These results show that a single Dijkstra execution can reasonably estimate typical evacuation performance but may underestimate the upper-tail evacuation times that govern life-safety design. For practical application to underground station design and evacuation-time verification, it is recommended that Dijkstra-based route generation be repeated across multiple tie-breaking realizations and that upper-percentile evacuation times be reported alongside the deterministic single-run result, so that the required safe egress time used in life-safety assessment reflects the variability inherent in equal-cost path selection.