Optimization and evolution of UAV insurance provision framework: Insights into multi-sector cooperation

Abstract

The rapid expansion of unmanned aerial vehicles (UAVs) presents considerable challenges in risk management. Although insurance is essential for mitigating the risks associated with UAV operations, aviation insurers face major obstacles in providing effective coverage due to insufficient actuarial data, limited expertise, and regulatory uncertainties. This study aims to optimize the UAV insurance provision framework to help address the issue of inefficient coverage. Through a comparative analysis of traditional and cooperative UAV insurance provision frameworks, the study identifies multi-sector cooperation as the most effective approach. This framework involves close cooperation among aviation insurers, the government, and UAV manufacturers. To examine the stability of this framework, an evolutionary game theory model is developed, with aviation insurers and the government as the main players. Factors such as cooperative profits, cooperative costs, and the benefits of free-riding are identified as pivotal to the framework's stability. The system's sensitivity to variations in these factors is demonstrated through simulations. The study also outlines a potential evolutionary path for the UAV insurance provision framework, emphasizing a phased approach that adapts to the evolving UAV landscape. This research offers valuable insights into optimizing UAV insurance provision and provides practical guidance for aviation insurers, policymakers, and UAV manufacturers in fostering cooperative strategies that enhance the overall safety and sustainability of UAV operations.