Runway Incursion Prediction Using Aircraft State Filtering

The aircraft's onboard system automatically performs traffic assessment and runway incursion prediction using its own sensors and processors, eliminating the need for continuous human monitoring and ground-based analysis. The system self-evaluates potential conflicts and provides timely alerts to the flight crew.

The patent replaces the mechanical human assessment process with an automated electronic system that uses onboard sensors, processors, and algorithms to detect, analyze, and predict potential runway incursions, providing faster and more consistent safety assessment.

The aircraft uses its existing onboard sensors and processing resources to perform traffic assessment and runway incursion prediction, eliminating the need for expensive external upgrades. The system leverages available computational resources efficiently to achieve accurate prediction without additional hardware investments.

The system focuses computational resources on predicting only the most critical and likely runway incursions rather than analyzing all possible scenarios, achieving high prediction accuracy for the most important cases while minimizing the processing power and cost requirements.

The system extracts and focuses only on the most relevant traffic information for runway incursion prediction, filtering out unnecessary data. By identifying and analyzing only the critical parameters and aircraft that pose potential risks, the system achieves comprehensive safety monitoring for runway incursions without the need to process all aircraft traffic data.

The patent segments the aircraft traffic analysis into distinct phases and focuses computational resources on the approach and landing phases where runway incursions are most likely to occur. By dividing the monitoring task into segments based on flight phase and risk level, the system achieves thorough safety monitoring during critical periods while reducing overall processing time and resource requirements.