We introduce the Ideal Flow Network (IFN) paradigm and Ideal Traffic Assignment (ITA) framework, a novel approach to modeling urban transportation that shifts the focus from traditional Origin-Destination (O-D) matrices to the intrinsic, structural properties of the network itself. The Ideal Traffic Assignment framework is a parsimonious model rooted in network structure, its topology, capacity and connectivity. By defining flow as a steady-state distribution on a directed graph, the model infers traffic patterns from probabilistic turning movements at each intersection. This ITA framework offers significant advantages over conventional methods, including greater data flexibility and scalability. We also provide a conceptual foundation for understanding traffic as an emergent property of a complex adaptive system. This highlights the limitations of intuitive solutions and underscores the need for rigorous mathematical modeling. It contrasts the IFN approach with traditional models, positioning IFN as a promising new tool for proactive urban transportation planning and policies in transportation planning and design.