Tehran faces the simultaneous challenges of traffic congestion, chronic air pollution, and severe financial and implementation constraints. Under such conditions, the key policy question is not merely to identify the most effective intervention, but to determine the implementation priority, complementary role, and phased sequencing of policies. To address this question, the present study evaluates eleven policy options, including seven stand-alone policies and four combined packages, over the 2024-2030 horizon.

The study employs a quantitative, two-stage design. First, the outcomes of the scenarios were extracted from an upstream hybrid simulator based on system dynamics, agent-based modeling, and machine learning; the criteria were then weighted using the CRITIC method, and the options were ranked using TOPSIS. In addition, several policy weighting structures were used to analyze the sensitivity of the results. Ten evaluation criteria were considered, covering three domains: transport effectiveness, reductions in pollution and health costs, and financial and implementation feasibility.

The findings indicate that the low-risk package (Scenario 8) is the most suitable initial option under balanced weighting. Local fleet emissions reduction (Scenario 6) constitutes the cornerstone of clean-air policy, while time-based travel demand management (Scenario 1) is the best starting point under severe financial constraints. The main innovation of the article lies in providing a practical framework for the economic-implementation prioritization of policies and designing a phased roadmap for sustainable transport under resource-constrained conditions.