The goal of this paper is twofold. First, we present a stochastic programming-based model that provides optimal design solutions for transportation networks in light of possible emergency evacuations. Second, as traffic congestion is a growing problem in metropolitan areas around the world, decision makers might not be willing to design transportation networks solely for evacuation purposes since daily traffic patterns differ tremendously from traffic observed during evacuations. This is especially true when potential disaster locations are limited in number and confined to specific regions (e.g. coastal regions might be more prone to flooding). However, as extreme events such as excessive rainfall become more prevalent everywhere, it is less obvious that the design of transportation networks for evacuation planning and congestion reduction is mutually exclusive. That is, capacity expansion decisions to reduce congestion might also be reasonable from an evacuation planning point of view. Conversely, expansion decisions for evacuation planning might turn out to be effective for congestion relief. To date, no numerical evidence has been presented in the literature to support or disprove these conjectures. Preliminary numerical evidence is provided in this paper.