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The US transportation sector is a major contributor to global greenhouse gas (GHG) emissions. As such, policymakers and stakeholder groups have proposed a number of policy instruments aimed at reducing these emissions. In order to fully evaluate the effectiveness of these policies, policymakers must consider both the direct responses associated with policy actions, and the indirect responses that occur through complex relationships within socioeconomic systems. In cases where multiple policy instruments are employed, these indirect effects create policy interactions that are either complementary or competing; policymakers need to understand these interactions in order to leverage policy synergies and manage policy conflicts. Analysis of these indirect effects is particularly difficult in the transportation sector, where system boundaries are uncertain and feedback among systems components can be complicated. This paper begins to address this problem by applying systems dynamics tools (in particular causal loop diagrams) to help identify and understand the role of feedback effects on transportation-related GHG reduction policies. Policymakers can use this framework to qualitatively explore the impacts of various policy instruments, as well as identify important relationships that can be later included in quantitative modeling approaches.