An en route capacity optimization model based on air traffic control process

Area of Science:

• Air Traffic Management
• Operations Research
• Automation Systems

Background:

• Airspace congestion and demand-capacity imbalances challenge current air traffic management.
• The need for advanced air traffic control automation systems is growing.

Purpose of the Study:

• To propose an en route air traffic control process model based on operational requirements.
• To optimize air traffic control by minimizing operation time, instantaneous density, and controller workload.

Main Methods:

• Developed an algorithm considering air traffic control schemes and instructions (climb, descent, speed restrictions).
• Modeled the complete air traffic control process, incorporating historical aircraft trajectory data.
• Utilized optimization objectives including operation time, instantaneous density, lateral displacement, and controller workload.

Main Results:

• Reduced total operation time by 18.6% compared to actual operations.
• Significantly decreased variance in lateral displacement and vertical separation.
• Improved en route air traffic capacity and balanced traffic flow density.

Conclusions:

• The model effectively addresses operational requirements in air traffic control.
• It enhances efficiency, reduces workload, and alleviates flight conflicts.
• The integration of historical data and controller command processes represents a key innovation.