Based on dynamic traffic assignment (DTA), this paper proposes a system-optimal multi-objective model for dynamic traffic guidance. Firstly, the physical road network is extended into a spatiotemporal network. By considering the impact of traffic congestion, a multi-objective linear programming model is formulated with the objectives of minimizing total travel time, total travel distance, total number of vehicles in the system, and total infrastructure maintenance cost. Subsequently, a solution method is devised, combining multiple objectives into a single composite objective function by weighted summation. Commercial solver like Gurobi is employed for single-objective linear optimization, and we iteratively calculate Pareto-efficient solutions and approximate the Pareto frontier. Ultimately, the precision and efficacy of the proposed model and solution method are validated through real-world travel data. Additionally, detailed analysis of the relationships between different objectives is conducted to reveal their impacts on the overall traffic guidance strategy.