Emergency conditions following an earthquake led to increased traffic congestion, blocked intersections, delays at signalized junctions, and damage to structures, especially high-rise buildings, which create obstacles on urban streets. This research investigates predictable scenarios arising from such emergency conditions with a focus on their impact on relief performance. The study addresses relief routing between supply and demand points based on travel time and distance as objective functions, examining different levels of traffic service in normal conditions, removal of directional constraints, and the presence of absolute or traversable obstacles with delays. Travel times for network links were calculated using a travel time-traffic flow relationship, while travel distances were based on link lengths. The scenarios were implemented using Dijkstra's algorithm within a GIS environment, employing network analysis tools and the origin-destination cost matrix capability to simulate various relief scenarios under emergency conditions. Variations in service levels showed that while travel distance remained constant across scenarios and objectives, travel time increased by 6% to 24%. Removing directional constraints reduced travel distance by 45% to 68% and travel time by 32% to 63%, whereas absolute obstacles with no travers ability led to increases of 110% in travel distance and at least 83% in travel time. The travel time objective under scenarios with traversable but delayed obstacles yielded better results, showing increases of 14% in distance and 7% in travel time relative to normal conditions. A comparison of objective values for relief vehicle routing under emergency conditions indicated the superiority of minimizing travel time over travel distance. The findings of this model can inform the development of emergency management policies at urban decision-making levels.