Prediction of Aircraft Take-off Weight using Machine Learning

Predicting aircraft Take-Off Weight (TOW) has been a long-sought task by aviation stakeholders, especially for operational and regulatory bodies involved in flight planning. Unfortunately, TOW being a sensitive parameter to operational trends and cost indices, aircraft operators tend to keep it confidential. In recent years, Machine Learning (ML...

Feasibility and accuracy of Received Signal Strength-based Multilateration for aircraft localization using crowdsourced data

To verify the aircraft position provided by Automatic Dependent Surveillance-Broadcast (ADS-B)<br/>transponders, multilateration (MLAT) technique incorporates time difference of arrival (TDOA) measurements at multiple ground-based receivers to estimate the corresponding distances between those and the aircraft. This approach requires precise...

On Understanding Environmental Inefficiencies in Air Traffic Management: A Causal Inference Approach

Addressing the increasingly urgent need for sustainable aviation solutions, this study explores operational innovations as a quicker and more scalable addition to novel zero-emission propulsion systems. Through the use of regression-based causal inference methods, this study aims to understand the relationship between flight fuelburn...

Dynamically Forecasting Airline Departure Delay Probability Distributions for Individual Flights using Supervised Learning

Punctuality is a key performance indicator for any airline. Hub-and-spoke airlines are particularly committed to on-time arrivals to guarantee passenger connections. Flights that are delayed at departure need to compensate for the lost time whilst airborne. Because fueling takes place well before scheduled departure, predicted departure delays...

Applying Large-Scale Weakly Supervised Automatic Speech Recognition to Air Traffic Control

The application of automatic speech recognition in the air traffic control domain has been researched extensively. However, its primary application remains in the training and simulation of air traffic controllers. This is due to the insufficient performance of automatic speech recognition in specific environments, such as air traffic control,...

Aircraft Tail-Specific Performance Modeling for Fuel Efficient Flight Operations in the Cruise Phase

Fuel-efficient flight operations and improved Air Traffic Management (ATM) operations are identified as one of the main pillars in achieving net-zero CO2 emissions by 2050. While considerable research has focused on airspace management and ATM operations, flight operations as managed by airlines have received little attention. <br/><br/>Accurate...

Modeling and analyzing the environmental impact of short-to-medium range air and ground transports

The emissions of the transport sector inside the EU-27 have risen by 33 % between 1990 and 2019. A modal shift from unsustainable transport towards more environmentally friendly transport modes can be taken as one solution to mitigate the overall emission of the transport sector. In this paper, multiple open-source models and databases are...

Automatic Speech Recognition for Air Traffic Control Using Open Data

Air Traffic Control (ATC) is tasked with ensuring safe separation between aircraft in a given Controlled Traffic Region (CTR). To achieve this an Air Traffic Controller (ATCo) verbally gives clearances using over the air communication. These clearances are kept track of by the ATCo using so-called ‘flight-strips’, which in modern systems are...

Streamlining multi-stop flights with ground transportation

Passenger transportation in Europe is often duplicated using modes of transportation which are environmentally inefficient. Quantifying the carbon dioxide emission inefficiencies of flights versus transit is beneficial to understand the potential savings of a modal shift. In this paper, we analyze the emissions in Europe from multi-stop flights...

Estimating wind fields using drones in a network: Estimating hyperlocal wind fields with on-board sensors on quadcopters

Charting hyperlocal wind using a drone is a challenge of increased attention as it unlocks potential in a variety of fields. In context of the METeo Sensors In the Sky project, this study proposes a method to estimate the magnitude and direction of wind using a quadcopter in hover and cruise without a dedicated wind sensor. Only on-board sensors...

Estimating Wind Fields Using Physically Inspired Neural Networks With Aircraft Surveillance Data

Wind estimation plays an important role in many aspects of our world, both for nowcasting and forecasting. This is also true for aircraft flight routes; where wind field knowledge can contribute to flight planning and safety. Aircraft can relay flight information back to ground-based receivers, from which local wind measurements can be derived....

Trajectory optimization to minimize the environmental impact of departing and arriving aircraft

The aviation industry faces the challenge of reducing its climate eects. This paper aims to determine whether optimizing flight trajectories can reduce the environmental impact of aircraft during the climb and descent phases. It addresses the research gap in sustainable flight trajectory optimization by combining state-of-the-art research on...

Automatic Dependent Surveillance for Drones: a Design and Capacity Study

The consumer drone sector is expected to grow rapidly in the coming decades. In Europe alone, it is predicted that in excess of seven million such machines will be flying by 2050. This poses a risk of conflict in dense airspaces, with both aircraft and other drones. Such a growing market provides a need to make drones visible to ATC and other...

Radio Frequency Fingerprinting for Aircraft Identification

Radio frequency fingerprinting has been identified as a method to increase integrity in aircraft surveillance while retaining its openness. One way to uniquely determine transmitting devices is to distill the device its radio frequency (RF) fingerprint by looking at the physical features of the message signal it transmits. This physical layer...

Uncertainty Modelling in Aircraft Trajectory Predictions

Several initiatives are being developed to shift the current paradigm in Air Traffic Management (ATM) from the tactical-based approach to more strategic-based coordination of flights. This transformation of the ATM system relies on the improvement of predictive models that predict the 4D-trajectory of an aircraft. Previous studies primarily...