Airlines to Cut Down on Tarmac Time
Airlines are increasingly focused on reducing time spent on the tarmac, and gate allocation is a key factor. While it may seem simple, determining the best gate for each plane is a complex challenge with many variables.
“With 15 gates and 10 aeroplanes, there are more than 570 billion possible arrangements,” says Dr. Joseph Doetsch, quantum computing lead at Lufthansa Industry Solutions. By optimising gate selection, airlines can reduce taxi times, cut fuel costs, and lessen emissions, helping passengers reach their destinations faster.
Typically, gates are assigned when flight schedules are set, often a year in advance. However, these assignments are reevaluated closer to flight day, as circumstances shift.
More Effective Gate Allocation Reduces Waiting Times
Selecting the ideal gate for each aircraft involves several considerations. Carriers may be assigned gates near their lounges, while flights with a high volume of connecting passengers are typically placed to minimise transfer times. Additionally, budget carriers often choose remote stands with lower parking fees to save on costs.
Other factors impacting gate assignment include the aircraft’s direction, type, expected runway, gate availability, staffing, and the scheduled movements of other aircraft. These variables are in flux, with delays requiring frequent reassignment, which can lead to increased waiting times and even cancellations.
Advancement in Machine Learning and Quantum Computing Technology
Given the complexity of gate assignment, it would seem logical for advanced technology to assist. However, many airports still manage this process manually. According to a survey by AeroCloud, 40% of airport executives use basic tools like Excel and Word to handle gate management.
However, some airlines are leading the way in adopting cutting-edge technology. American Airlines, for example, implemented its Smart Gating system at Dallas Fort Worth International Airport last year. This machine-learning-based system uses real-time data to assign gates quickly, reducing the processing time from four hours to just 10 minutes. The system’s efficiency has shortened taxi times by 20%, saving an estimated 1.4 million gallons of jet fuel annually.
Lufthansa Industry Solutions is also exploring quantum computing, which uses the unique properties of qubits to solve specific problems more rapidly than traditional computers. Quantum algorithms could be the answer to optimizing gate assignment even in large, busy airports, adjusting solutions in real-time as conditions change.
“Our initial simulations show that optimised quantum computing solutions could reduce passenger transit times by nearly 50%,” notes Dr. Doetsch. Lufthansa is now evaluating which quantum systems will work best for this application.
Optimising Capacity with Advanced Solutions
As airport capacity becomes a growing concern, these technological advancements could reduce the need for physical expansion. “Capacity is a big issue for many airports. Even if they wanted to introduce new carriers or destinations, physical expansion is often not feasible,” says AeroCloud’s Mr. Richardson. “Optimising current resources is essential.”
At Brookfield Aviation International, we recognise the transformative impact that innovative technologies like machine learning and quantum computing will have on the aviation sector. These advancements in gate management and resource optimisation align with our mission to streamline operations, enhance efficiency, and promote sustainable practices across the aviation industry.
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