Conflict-Free Aircraft Trajectory Planning Using ADS-B Traffic Data
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Solution Overview
Problem
Current air traffic control systems rely heavily on ground-based radar, leading to increased workload, fuel burn, emissions, and noise due to frequent interventions by air traffic controllers to maintain separation between aircraft, and pilots lack comprehensive information for efficient flight trajectory planning.
Innovation Solution
A system and method for generating multiple conflict-free flight trajectories that consider various operational requirements, including fuel efficiency and time efficiency, using Automatic Dependent Surveillance—Broadcast (ADS-B) data and Standard Avoidance Intervals (SAI) to minimize interventions by air traffic controllers, while incorporating additional information like wind, weather, and airspace restrictions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If ground-based radar systems are used to monitor aircraft positions, then air traffic control can maintain separation between aircraft, but controller workload and intervention frequency increase
Solution Approach 1:
The system enables aircraft to autonomously determine conflict-free trajectories by providing them with state vector data of other aircraft and computational tools. Instead of controllers manually monitoring and directing each aircraft, the aircraft self-manage separation by evaluating multiple trajectory options against real-time traffic data and selecting optimal paths that avoid conflicts.
Solution Approach 2:
The system performs preliminary trajectory analysis and conflict detection before aircraft actually enter conflicting situations. By continuously calculating potential conflicts based on projected paths and state vectors, the system identifies and resolves separation issues in advance, allowing aircraft to adjust their trajectories proactively rather than reactively during controller interventions.
2Reliability
If air traffic controllers intervene frequently to maintain separation, then safety is ensured, but fuel burn and emissions increase
Solution Approach 1:
Aircraft autonomously manage their own separation and trajectory optimization without requiring continuous controller interventions. The onboard systems evaluate conflict-free trajectories and execute adjustments independently, eliminating the need for pilots to respond to frequent speed changes, level segment assignments, or off-course vectors that would increase fuel consumption.
Solution Approach 2:
The system optimizes flight parameters such as speed, altitude, and trajectory path to minimize fuel burn while maintaining safety. By continuously adjusting these parameters based on real-time state vector data and conflict predictions, the system identifies fuel-efficient trajectories that avoid conflicts without requiring energy-intensive corrective maneuvers or deviations from optimal flight paths.
3Ease of operation
If pilots plan trajectories without knowledge of other aircraft, then flight planning is simpler, but conflicts require disruptive ATC interventions
Solution Approach 1:
The system provides pilots with automated conflict-free trajectory recommendations that already account for other aircraft positions and movements. Instead of manually complex planning to avoid conflicts, the onboard system processes state vector data from other aircraft and presents optimized trajectory options that are inherently conflict-free, combining simplicity with high efficiency.
Solution Approach 2:
The system continuously receives real-time state vector data from other aircraft via ADS-B and uses this feedback to dynamically adjust and update conflict-free trajectory recommendations. This closed-loop feedback mechanism ensures that trajectory plans remain optimal and conflict-free throughout the flight, automatically adapting to changing traffic conditions without requiring manual replanning or disruptive ATC interventions.
4Loss of information
If ADS-B systems broadcast state vector data, then aircraft can receive real-time traffic information, but system complexity and data processing requirements increase
Solution Approach 1:
The system automatically processes ADS-B state vector data from multiple aircraft and autonomously generates conflict-free trajectory recommendations without requiring manual analysis. The onboard computer performs all necessary data fusion, conflict detection, and trajectory optimization calculations, presenting processed results to pilots in an easily interpretable format that transforms complex raw data into actionable flight guidance.
Solution Approach 2:
The system performs preliminary processing and filtering of ADS-B data to identify only the relevant state vectors and potential conflicts before presenting information to pilots. By pre-processing the data stream to extract critical information about nearby aircraft and potential trajectory conflicts, the system reduces the complexity of real-time decision-making while maintaining complete situational awareness.
Data Source
AI summary
Systems and methods of the present invention are provided to generate a plurality of flight trajectories that do not conflict with other aircraft in a local area. Interventions by an air traffic control system help prevent collisions between aircraft, but these interventions can also cause an aircraft to substantially deviate from the pilot's intended flight trajectory, which burns fuels, wastes time, etc. Systems and methods of the present invention can assign a standard avoidance interval to other aircraft in the area such that a pilot's aircraft does not receive an intervention by an air traffic control system. Systems and methods of the present invention also generate a plurality of conflict-free flight trajectories such that a pilot or an automated system may select the most desirable flight trajectory for fuel efficiency, speed, and other operational considerations, etc.