Policy Emulation and Learning in Autonomous Vehicle Policy in the American States

• In Event: Governance of Science, Technology, and AI

Abstract

The evolution of transportation systems marked by the rise of autonomous vehicles (AVs) and supported by technologies such as intelligent mapping and the integration of IoT, machine learning, and AI offers many social benefits. However, the transformative potential of AVs also brings forth socio-political complexities that necessitate novel collaborative governance among various stakeholders. Within this dynamic context, this study delves into how emerging AV policies in the states are influenced by policy emulation and learning. Specifically, this study explores the role of third-party organizations and interstate collaborations in facilitating policy learning, providing actionable insights for policymakers. We find that states with successful AV policies tend to be emulated more frequently than those struggling with their policies. Further, interstate actors are facilitating both learning and emulation. The findings of this study not only contribute to the advancement of academic research on policy learning but hold practical relevance in an era marked by transformative changes in transportation.

Author

• Pedro Robles, Pennsylvania State University
  Presenting Author