Hybrid Quantum-Classical Path Planning for Air Traffic Control
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Solution Overview
Problem
Current aircraft path planning systems face challenges in optimizing the management of aircraft paths, particularly in high-density air traffic scenarios, leading to congestion, increased conflicts, and cascading delays.
Innovation Solution
The integration of classical and quantum computing systems to leverage quantum annealing for an iterative path planning technique. This approach uses classical computing to calculate distances and generate maneuverability options, while quantum computing selects the lowest-cost options to minimize distance to a target while maintaining aircraft separation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the number of aircraft utilizing a common path is increased, then the productivity of the air traffic system is improved, but the device complexity and conflict management difficulty increase rapidly
Solution Approach 1:
The patent segments the path planning problem into discrete time steps and spatial zones, allowing the system to manage complex air traffic by breaking it down into manageable segments that can be optimized independently and then integrated into a complete solution
Solution Approach 2:
The system dynamically adjusts aircraft paths and schedules in real-time based on current traffic conditions, weather, and constraints, allowing the path planning solution to adapt continuously rather than being static, thereby managing complexity through flexibility
2Reliability
If time delays are added to handle congestion and conflicts, then the reliability of collision avoidance is improved, but the loss of time and productivity deteriorate due to cascading delays
Solution Approach 1:
The system performs preliminary path planning and conflict detection before aircraft actually encounter conflicts, allowing delays and route adjustments to be scheduled in advance in a coordinated manner, preventing cascading delays rather than reacting to them after they occur
Solution Approach 2:
The system continuously monitors aircraft positions and path conflicts, using this feedback to dynamically adjust schedules and routes, ensuring that delay management is based on real-time conditions rather than static pre-planning, thereby minimizing unnecessary time losses
3Adaptability or versatility
If the number of maneuverability options is increased to improve path planning flexibility, then the adaptability of the system is improved, but the computational complexity and difficulty of detecting and measuring optimal paths increases
Solution Approach 1:
The patent applies different levels of maneuverability options to different aircraft based on their specific situations, constraints, and positions, rather than allowing all aircraft to have the same full set of options, thereby reducing overall computational complexity while maintaining necessary adaptability where required
Data Source
AI summary
Disclosed herein are systems and methods for optimizing air traffic control managing using a Quantum Annealing-based iterative path planning technique and algorithm that involves both classical and quantum computation components. The classical component can calculate the distances between aircraft and the target destination from a set of new, possible properties, such as aircraft location. The quantum component can select from the new, possible properties to minimize the distance of the aircraft to the target destination while ensuring adequate separation between aircraft. The algorithm can utilize qubits to represent maneuverability options for aircraft. The maneuverability options may be partitioned into a set of multiple qubits per aircraft. Each set may include a plurality of qubits that are representative of the sub options. The algorithm can utilize Quadratic Unconstrained Boolean Optimization (QUBO) to find the lowest cost-energy maneuverability option.