This study explores the use of Many Objective Robust Decision Making (MORDM) to manage deep uncertainty in transport climate policy analysis. The focus is on policies supporting Sweden's ambition to achieve net-zero emissions by 2045. A case study analysis demonstrating how MORDM can be applied to a simplified policy analysis tool for the Swedish transport sector is performed. Candidate policies are generated using a multiobjective evolutionary algorithm. This algorithm searches for policies that meet the climate target while trying to minimize adverse impacts on driving-based accessibility and limiting the use of biofuels and electricity for a reference scenario for 2040. The candidate policies' robustness and vulnerabilities are then assessed by evaluating them over a set of 10,000 scenarios spanned by deeply uncertain scenario factors and model relationship assumptions. The results highlight tradeoffs among policy objectives within scenarios, as well as tradeoffs in robustness of various policy objectives over the scenario set. For all policies, the main vulnerability in terms of reaching the climate target relates to vehicle electrification rates. However, the MORDM policies do not distinctly outperform policies identified by a previous study by the Swedish Transport Administration applying the same tool. MORDM provides a framework for systematic evaluation of policy robustness and vulnerabilities under varying future uncertainties, something which has not previously been explicitly considered. The study contributes to a better understanding of the trade-offs and dependencies inherent in achieving robust transport climate policies.