Automation technology is emerging, but the adoption rate of autonomous vehicles (AV) will depend upon how policymakers and the government address various challenges such as public acceptance and infrastructure development. This study follows a five-stage method to understand these barriers to AV adoption. First, based on a literature review followed by discussions with experts, ten barriers are identified. Second, the opinions of eighteen experts from industry and academia regarding inter-relations between these barriers are recorded. Third, a multicriteria decision making technique, the grey-based Decision-making Trial and Evaluation Laboratory (Grey-DEMATEL), is applied to characterize the structure of relationships between the barriers. Fourth, robustness of the results is tested using sensitivity analysis. Fifth, the key results are depicted in a causal loop diagram (CLD), a systems thinking approach, to comprehend cause-and-effect relationships between the barriers. The results indicate that the lack of customer acceptance (LCA) is the most prominent barrier, the one which should be addressed at the highest priority. The CLD suggests that LCA can be mitigated by addressing two other prominent and more tangible barriers – lack of industry standards and the absence of regulations and certifications. The study’s contribution lies in demonstrating that the barriers to AV adoption do not exist in isolation but are linked with each other in overlapping loops of cause and effect relationships. These insights can help different stakeholders in prioritizing their endeavors to expedite AV adoption. From the methodological perspective, this is the first study in the transportation literature that integrates Grey-DEMATEL with systems thinking.