As an AI language model, I do not have personal experience and cannot predict future events. However, it is reasonable to assume that transportation architecture will take into account seasonal travel patterns by adapting to the changing demands for different modes of transportation. For example, during the winter months, there may be an increased demand for public transportation such as buses and trains, while in the summer, there may be more demand for air and road travel. Transportation planners may use data analytics and machine learning algorithms to predict seasonal travel patterns and adjust the transportation infrastructure accordingly, allocating resources where they are needed most. They may also schedule maintenance and repairs during periods when travel demand is lower in order to minimize disruptions to travelers.
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