Multidimensional Coupling Model for Quantitative Ground Risk Assessment of Urban Low-Altitude Logistics UAVs

This paper proposes a multi-dimensional coupled quantitative model for the ground risk of urban low-altitude logistics drones, integrating public acceptance, to address the difficulty of existing assessment methods in integrating dynamic environmental and socio-psychological factors. The model combines physical, economic, and social dimensions through a grid-based airspace segmentation and multi-source data framework. The physical module quantifies crash patterns and wind resistance impact, the economic module assesses direct and indirect losses, while the social module converts public psychological tolerance into spatial correction factors. Based on the theory of "social amplification of risk," an inter-dimensional coupling mechanism is established, and a dynamic risk map generated using GIS. Case simulations show that wind resistance can expand the high-risk area for cargo falls by approximately 15%, the high-risk area for gliding overlaps with the public's psychologically sensitive area by 83%, and low public acceptance can lead to an increase in the overall risk level by 1–2 levels. Further, the pure physical risk model underreported 35%. This model outperforms traditional methods in terms of the comprehensiveness and spatial accuracy of risk identification, providing quantitative decision support for risk management and route planning in low-altitude logistics systems.