Urban Air Mobility Fusion Platform for Collision Avoidance
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Solution Overview
Problem
The increasing density of aerial vehicles in urban airspaces poses a challenge for effective air traffic management, requiring advanced solutions for coordinating and monitoring air traffic to prevent collisions and ensure safe operation.
Innovation Solution
An urban air mobility system comprising cooperative and data-consuming aerial vehicles, a detection platform, and a fusion platform that aggregates position data from various sources using sensors like radar, lidar, and cameras to generate an accurate air traffic scenario, allowing for improved situational awareness and reduced sensor requirements on individual vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If each aerial vehicle is equipped with advanced sensors for detection, then the measurement precision of position information is improved, but the device complexity and cost increase
Solution Approach 1:
The patent merges the sensor detection functions of multiple aerial vehicles into a single fusion platform. Cooperative aerial vehicles transmit their sensor data to the fusion platform, which aggregates and processes all position information from various sources (radar, lidar, cameras) to generate a unified air traffic scenario, eliminating the need for each vehicle to maintain complex sensor suites
Solution Approach 2:
The fusion platform acts as an intermediary between the detection platforms and the aerial vehicles. It receives raw sensor data from cooperative vehicles and the detection platform, processes and fuses this information, then distributes the synthesized air traffic scenario to all registered vehicles, including data-consuming vehicles that lack detection capabilities
2Reliability
If the detection platform monitors all flight objects independently, then the reliability of air traffic monitoring is improved, but the loss of information increases due to data processing requirements
Solution Approach 1:
The system segments the air traffic monitoring function into two parts: detection platforms that collect raw sensor data from flight objects, and the fusion platform that processes and integrates this data. This segmentation allows each component to focus on specific tasks, reducing overall processing complexity while maintaining comprehensive monitoring
Solution Approach 2:
The fusion platform performs multiple functions: it fuses data from different sensor types (radar, lidar, cameras), integrates information from multiple aerial vehicles, detects non-cooperative vehicles, and distributes processed information to all registered vehicles. This multi-functionality consolidates what would otherwise require multiple separate processing systems
Data Source
AI summary
An urban air mobility system includes aerial vehicles, a detection platform, and a fusion platform. The aerial vehicles include one cooperative aerial vehicle and one data consuming aerial vehicle. The detection platform detects a position of flight objects and transmits first data indicative of the position of the detected flight objects to the fusion platform. The cooperative aerial vehicle detects a relative position of flight objects in its surroundings and transmits second data indicative of the relative position of detected flight objects to the fusion platform. The fusion platform fuses the first data and the second data and generates an air traffic scenario. The data consuming aerial vehicle and the cooperative aerial vehicle receive the air traffic scenario from the fusion platform.