Dynamic Airspace Planning for Fuel-Efficient Flight Paths
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Solution Overview
Problem
Current flight path planning for aircraft is largely manual and based on static pre-filed flight plans and voice instructions from air traffic control, which are not optimized for factors like fuel consumption or changing flight conditions.
Innovation Solution
A system and method for dynamically generating and selecting optimized flight paths using an airspace model with an array of nodes, where each node represents a distinct position in the airspace, allowing for real-time planning and replanning of flight paths based on various parameters such as fuel efficiency and safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual processes are used for flight path determination based on pre-filed flight plans and voice instructions, then flight paths can be established with human oversight, but the flight paths are not optimized for fuel consumption or flight time and cannot account for changing flight conditions
Solution Approach 1:
The system implements dynamic flight path generation by continuously receiving real-time flight condition data (weather, air traffic, aircraft performance) and automatically recalculating optimized routes. The processor-based system updates flight paths dynamically rather than relying on static pre-filed plans, enabling adaptation to changing conditions while optimizing fuel consumption through algorithmic route selection.
Solution Approach 2:
The patent replaces manual ATC voice instructions and pilot judgment with an automated processor-based system that uses algorithms to generate and optimize flight paths. This substitution of mechanical/human processes with electronic computation enables continuous optimization of fuel consumption and automatic adaptation to changing flight conditions without human intervention.
2Ease of operation
If static pre-filed flight plans are used, then flight paths can be established in advance, but they cannot be updated to reflect changing flight conditions
Solution Approach 1:
The system performs preliminary flight path planning by pre-calculating multiple candidate routes and storing them in the database before flight execution. These pre-computed paths are then dynamically selected and adjusted during flight based on real-time conditions, combining the benefits of advance preparation with adaptive responsiveness to changing circumstances.
Solution Approach 2:
The system transitions from static pre-filed plans to dynamic flight path management by continuously monitoring flight conditions and automatically selecting or modifying from pre-computed candidate routes. The processor-based system enables real-time updates while maintaining the efficiency of pre-planning through algorithmic route optimization.
3Productivity
If automated systems are implemented for dynamic flight path generation, then fuel efficiency and adaptability improve, but system complexity increases
Solution Approach 1:
The automated system is segmented into distinct functional modules: a database for storing flight path data, a processor for executing optimization algorithms, and interfaces for receiving real-time flight condition data. This modular architecture manages system complexity by dividing the automated flight path generation into manageable, independent components that can be developed and maintained separately.
Solution Approach 2:
The patent uses an airspace model comprising an array of nodes as an intermediary representation between raw flight condition data and optimized flight paths. This node-based model simplifies the complex task of path optimization by providing a standardized geometric framework that the processor can efficiently algorithmize, reducing the computational complexity of generating optimized routes.
Data Source
AI summary
A method for dynamic airspace planning is performed by one or more processors, and includes identifying, in an airspace model that includes an array of nodes, a set of path elements. Each path element connects a pair of adjacent nodes in the array. The method includes obtaining, for each aircraft in a set of aircraft, a respective current position on a path element. The set of aircraft may include thousands of manned and/or unmanned aircraft. The method includes obtaining, for each aircraft, a respective final position on a path element; and enumerating, for each aircraft, a respective set of flight paths. Each flight path includes one or more path elements, and extends from at least the current position of a respective aircraft to the final position of the respective aircraft. The method includes determining, for each aircraft, a respective optimal flight path based on the respective set of flight paths.