Ground Collision Avoidance With Airport Map Filtering
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Solution Overview
Problem
Pilots face challenges in seeing wingtips of their aircraft while taxiing, leading to potential collisions with obstructions due to curved taxiways and increased air traffic, with existing collision avoidance systems generating nuisance alerts that can be ignored, risking actual collisions.
Innovation Solution
A ground collision avoidance system using an airport moving map database to correct aircraft and obstacle positions, predict collision risks, and reduce nuisance alerts by considering surface operation rules and geometry, employing sensors and a controller to provide collision warnings via a display device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If collision avoidance system generates alerts based solely on heading and ground speed, then collision detection capability is improved, but nuisance alert rate increases
Solution Approach 1:
The system performs preliminary actions by retrieving airport surface geometry data and operational rules before generating collision alerts. The controller pre-fetches taxiway centerline coordinates, runway thresholds, and other spatial information to establish a contextual framework for evaluating potential collisions, ensuring alerts are generated only after verifying actual collision risk against known surface constraints.
Solution Approach 2:
The airport surface geometry data and operational rules serve as an intermediary between raw collision detection algorithms and final alert generation. This intermediary layer filters out false positives by comparing predicted collision paths against actual taxiway geometries and operational constraints, allowing the system to distinguish between genuine collision risks and spurious alerts caused by curved taxiways or non-intersecting paths.
2Ease of operation
If pilots pay less attention to collision alerts due to nuisance alerts, then ease of operation is improved, but collision avoidance reliability deteriorates
Solution Approach 1:
The system implements feedback by continuously monitoring aircraft position, velocity, and surface geometry to dynamically adjust alert generation. By comparing real-time aircraft states against pre-retrieved operational rules and geometry data, the system provides accurate feedback on actual collision risk, enabling pilots to trust alert relevance and maintain appropriate attention levels without being overwhelmed by false alarms.
3Adaptability or versatility
If aircraft taxiing on curved taxiways with intersections, then adaptability to airport operations is improved, but collision risk detection complexity increases
Solution Approach 1:
The system performs preliminary retrieval of airport surface geometry data including taxiway centerline coordinates, runway thresholds, and operational rules before collision assessment. This pre-fetching of contextual information simplifies the detection process by having reference data ready, reducing the computational complexity of evaluating collision risks on curved and intersecting taxiways.
Solution Approach 2:
The airport surface geometry and operational rules act as an intermediary that simplifies complex collision detection on curved taxiways. By providing a reference framework of valid aircraft paths and operational constraints, this intermediary enables the system to adapt to various airport configurations without proportionally increasing detection complexity, as the geometry data encodes the acceptable flight paths.
Data Source
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AI summary
A ground collision avoidance method in an ownship vehicle is disclosed. The method includes: retrieving position measurements for the ownship vehicle and for a dynamic obstacle; retrieving mapping data from an airport map database that includes coordinate data for airport travel pathways; adjusting a position measurement for the ownship vehicle and a position measurement for the dynamic obstacle based on coordinate data retrieved from the airport map database and historical aircraft movement data; predicting a series of future positions for the ownship vehicle that are constrained by airport surface operation rules; predicting a series of future positions for the dynamic obstacle that are constrained by airport surface operation rules; calculating whether a potential collision is imminent; and causing a collision alert to be displayed when the processor has determined that a potential collision between the ownship vehicle and the dynamic obstacle is imminent.