城市低空飞行汽车环境感知方案综述

With the rapid development of the urban low-altitude economy, flying cars are increasingly valuable in application such as disaster rescue, environmental monitoring, and traffic management. Environmental perception remains the core prerequisite and major challenge for their intelligence. This paper provides a systematic review of the current status and trends in this field. It firstly analyzes the function demand of typical flight scenarios, including navigation between buildings, operation in adverse weather, and multi-vehicle coordination, and identifies three key challenges, which are accurate perception in complex dynamic environments, degradation of sensor performance under disturbances, and limited computational power and energy constraints of onboard platforms. To address these, the study examines key technical approaches such as multi-sensor fusion, lightweight AI algorithms, and collaborative perception, highlighting their principles and implementation strategies based on cutting-edge research. The findings show that innovative technical solutions can effectively enhance the reliability, accuracy, and robustness of perception systems under stringent resource limitation. Finally, the paper discusses current technological bottlenecks and suggests future research directions to provide reference for the development of environmental perception technology for urban low altitude flying vehicles.