This research aims to advance traffic assignment and network design by extending existing models and methods to account for flow metering and spillback effects. Four key objectives are addressed: (1) modifying state-of-the-art traffic assignment (TA) algorithms to accommodate the Strategic Traffic Assignment with Queuing (STAQ) model, to enhance accuracy without significantly increasing computational complexity; (2) developing methods for Road Network Design Problems (RNDP) that incorporate STAQ to provide more reliable predictions compared to traditional steady-state models; (3) investigating Braess' Paradox Detection Problems (BPDP) by allowing not only road closures but also capacity reductions, with STAQ applied to improve decision-making at the network design level; and (4) extending the current RNDP with the modifications allowed in our BPDP model, formulating a general network design problem, enabling optimization of network supply through both expansion and contraction. Finally, the research will demonstrate and compare the new methods with traditional network planning systems in real-world scenarios, assessing their performance in terms of solution quality, convergence, and scalability. Through these objectives, the research aims to provide better tools for strategic network design that are more accurate and adaptable to complex urban environments.