Real-Time Aircraft Route Planning via Node Subset Selection
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Solution Overview
Problem
Current systems fail to compute cost-optimal flight routes for low-flying aircraft in real-time due to high computational complexity, particularly for military transport planes, which are under increased stress and risk during low-level flights, requiring efficient route planning to minimize risks and adhere to aircraft limitations.
Innovation Solution
A process and system that determine a cost-minimized flight route by creating a raster set of topographical points, assigning nodes with approach directions, and using a modified shortest path algorithm to consider only the k most cost-effective nodes, reducing computational time and accounting for aircraft limitations and threat risks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a standard shortest path algorithm is used to compute the optimal flight route considering all N nodes (approach directions) for each raster point, then the route optimization precision is improved, but the computational time increases significantly
Solution Approach 1:
The patent applies partial action by computing only the k most cost-effective nodes (where k < N) for each raster point instead of all N approach directions. This partial computation achieves satisfactory route optimization precision while significantly reducing computational time, making real-time route planning feasible for low-flying aircraft.
Solution Approach 2:
The patent changes the parameter from considering all N nodes to considering only k nodes (k < N) per raster point. This parameter change transforms the computational problem from intractable to solvable in real-time, while maintaining acceptable route optimization quality through adaptive selection of the top k cost-effective paths.
2Reliability
If all N approach direction nodes are considered for each raster point to ensure complete route exploration, then the route safety is improved, but the device complexity increases
Solution Approach 1:
The system computes only the k most cost-effective nodes instead of all N nodes, reducing computational complexity while maintaining sufficient route safety through adaptive selection of promising paths based on cost criteria.
Solution Approach 2:
The patent extracts only the k most relevant cost-effective nodes from the complete set of N approach directions, discarding less promising paths. This extraction reduces system complexity while preserving route safety by focusing computational resources on the most viable options.
3Object-affected harmful factors
If the aircraft flies at low altitude to avoid detection by radar and SAM stations, then the detection risk is reduced, but the flight time increases and maneuverability decreases
Solution Approach 1:
The patent implements dynamic route planning that adapts to changing threat conditions and aircraft state. The system continuously recomputes optimal routes considering low-altitude flight requirements, dynamically adjusting the path to balance detection risk reduction with flight time and maneuverability constraints.
Solution Approach 2:
The patent changes the flight parameters by incorporating altitude-dependent cost functions that reflect the trade-off between low-altitude safety (reduced detection risk) and flight performance (speed and maneuverability). The cost model dynamically adjusts based on threat levels and aircraft capabilities.
Data Source
AI summary
A process and system for the planning a cost-minimized aircraft flight route between a starting point and end point takes into account costs associated with the flight route, no-fly zones and flight corridors, and aircraft limitations. A raster set is determined which comprises topographical points between the starting and end points, and costs associated with the respective raster points are determined. N nodes are determined for each raster point of at least one subset of the raster set, such nodes being associated with approach directions of the raster point by the aircraft. Possible take-off directions of the raster point are defined, taking into account the minimum turning radius of the aircraft, as a function of the approach direction. A cost-minimized flight route is determined by means of a shortest path algorithm, taking into account only the k most cost-effective nodes (k<N) for a raster point.