Mid-Air Collision Risk for Urban Air Mobility: A Review

Highlights: What are the main findings? This review summarizes the international research conducted on mid-air collision risk and safety modeling for Urban Air Mobility (UAM), covering airspace structuring, enabling technologies, and collision-avoidance frameworks. It identifies common patterns and limitations across existing approaches, and clarifies how the current risk models, airspace designs, and operational technologies interact within the emerging UAM systems. What are the implications of the main findings? This analysis provides a consolidated reference for researchers, method developers, and regulators seeking to understand the state of safety research and remaining challenges in urban low-altitude operations. The outlined research gaps and trends can help guide future studies toward more integrated, data-driven, and safety-oriented frameworks for UAM management. Urban Air Mobility (UAM) introduces new safety challenges as small unmanned aircrafts begin to operate at high density in complex urban environments. Traditional air traffic management (ATM) systems developed for manned aviation are unable to accommodate the autonomy, mission diversity, and dynamic obstacle conditions typical of low-altitude operations. This review examines recent research on mid-air collision risk and airspace safety modeling for UAM and identifies key challenges in adapting existing safety concepts to small-scale and autonomous flight. The study compares international management frameworks of the United States, Europe, and China. Then analyzes representative airspace structures such as Free, Layered, Zoned, and Pipeline configurations. It further reviews deterministic and probabilistic separation models, geometric and optimization-based avoidance strategies, and structured airspace approaches such as the virtual-tube concept for coordinated swarm navigation. The findings highlight the lack of integrated models that couple human, energy, and communication factors into quantitative risk assessment. The paper concludes by outlining future research needs in uncertainty modeling, digital-twin simulation, and interoperability to support safe and scalable UAM development.