The growing tension between heritage protection and transportation demands in historic urban districts poses significant planning challenges. This study addresses this issue by developing a multi-modal transportation coordination optimization model from a dual protection–renewal perspective. The model integrates three objectives—minimizing comprehensive impacts, maximizing traffic utility, and minimizing travel costs—encompassing both time and monetary expenditure. A linear weighting method is used to consolidate these into a single objective function, which is then solved with a particle swarm optimization algorithm. Applied to the historic urban districts of Yangzhou, China, the model evaluates and compares three typical policy-oriented transport development strategies: the protection strategy, the balanced strategy, and the renewal strategy. The protection strategy minimizes the comprehensive impact on the historic environment and total social costs, making it suitable for core areas with high conservation pressure. The balanced strategy achieves the optimal trade-off among comprehensive impact, traffic utility, and total cost, serving as a baseline for most historic districts. The renewal strategy, while improving traffic utility, significantly undermines historical integrity and increases total costs, and is therefore applicable only to peripheral areas with low protection pressure. The study concludes that strategy selection is inherently context-dependent, considering local heritage values, spatial constraints, and travel demand patterns. This method provides a transferable decision-support framework for sustainable transportation planning in historic urban districts.