Flight Plan Time Slot Allocation for Fuel Waste Reduction
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Solution Overview
Problem
Aircrafts often waste fuel due to unnecessary delays caused by long takeoff queues and unavailable gates at departure and arrival airports, which existing systems fail to optimize effectively.
Innovation Solution
A system and method that determine an optimal flight time slot for an aircraft by analyzing traffic density and surface delays using real-time position data, scheduled flight plans, and weather forecasts, incorporating a 4D trajectory flight plan manager to predict traffic and surface delays, and selecting the time slot with the least traffic density and delays.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If aircraft depart according to traditional scheduling, then flight operations proceed in an organized manner, but aircraft experience unnecessary delays and fuel waste due to long takeoff queues and unavailable gates
Solution Approach 1:
The system performs preliminary analysis of traffic density and gate availability for multiple future time slots before the aircraft actually departs. By calculating expected traffic density at merging points and gate availability in advance, the system enables the aircraft to select an optimal departure time that avoids future congestion, thereby preventing fuel waste from unnecessary delays while maintaining organized flight operations
Solution Approach 2:
The system dynamically adjusts departure time recommendations based on real-time and forecasted traffic conditions. Instead of using fixed scheduling, the system continuously evaluates traffic density at merging points and gate availability at arrival airports for multiple potential departure times, allowing the aircraft to adapt to changing traffic patterns and select the most efficient departure window
2Reliability
If aircraft wait in long queues to take off, then air traffic control maintains safe separation, but fuel is wasted and operational efficiency decreases
Solution Approach 1:
The system calculates expected traffic density at merging points for multiple future time slots before the aircraft departs. By knowing in advance when traffic density will be lower, the aircraft can select a departure time that minimizes waiting in queues while still maintaining safe separation requirements set by air traffic control, thereby reducing delay time without compromising safety
3Ease of operation
If existing scheduling systems are used, then flight plans are established, but they fail to optimize departure times to avoid traffic congestion and gate unavailability
Solution Approach 1:
The system incorporates feedback loops that continuously monitor actual traffic density and gate availability against predicted values. By comparing expected traffic density at merging points and gate availability at arrival airports with actual conditions, the system refines its predictions and provides increasingly accurate departure time recommendations, thereby optimizing operational efficiency while maintaining ease of flight plan establishment
Solution Approach 2:
The system evaluates multiple departure time parameters to identify the optimal departure window. By analyzing traffic density and gate availability across different time slots and selecting the parameter (departure time) that minimizes both traffic density and delay, the system transforms traditional single-time scheduling into multi-parameter optimization, thereby improving operational efficiency without complicating flight plan establishment
Data Source
AI summary
A system and method for determining an optimum flight slot for an aircraft are provided. The method, for example, may include, but is not limited to, receiving flight plan input data from a client device, generating a flight plan based upon the flight plan input data, the flight plan including a plurality of fixes, determining a plurality of time slots based upon the flight plan input data, determining a traffic density for each fix along the flight plan for each of the plurality of slots, the traffic density based upon a number of aircraft within a bounding area containing each respective fix, determining the optimum flight time slot from the plurality of time slots based upon a weighted summation of the traffic density for each fix along the flight plan for each of the plurality of slots, and transmitting the optimum flight time slot to the client device.