Estimating landing time based on historical data: Aerlabs

This report is a document that presents the project Estimating landing time based on historical data. We want to succeed in designing and implementing a system based on requirements posed by our client AerLabs. The main goal we are researching is whether we can accurately predict the landing time and runway<br/>of arriving flights at Amsterdam...

Enabling Continuous Descent Operations in High-Density Traffic

The Air Traffic Management (ATM) community strives to reduce the environmental impact per flight. Continuous Descent Operation (CDO) has been identified by the ATM community as one of the operational improvements that could reduce aviation’s environmental impact, both in terms of aircraft noise and gaseous emissions. In the current ATM system,...

Arrival Management Support in the Presence of Prediction Uncertainty

Future concepts for Air Traffic Management (ATM) foresee—and even mandate—an increase in the distance from the destination airport at which the ATM system should start planning the arrival sequence and arrival time of inbound flights. By increasing the horizon beyond one hour before arrival, it becomes possible to timely adjust the flight path...

Improving Pedestrian Prediction Models with Self-Supervised Continual Learning

Autonomous mobile robots require accurate human motion predictions to safely and efficiently navigate among pedestrians, whose behavior may adapt to environmental changes. This paper introduces a self-supervised continual learning framework to improve data-driven pedestrian prediction models online across various scenarios continuously. In...

Near Real-Time Impact Point Prediction for the Flight Termination System of the DART XL Sounding Rocket

A flight termination system (FTS) is one of the most important safety features on a launch vehicle, as it allows for the vehicle's flight to be terminated in a controlled way when predetermined safety criteria or boundaries are exceeded. Currently, T-Minus Engineering B.V. aims to develop a custom flight termination system for the Dart payload...

Closed-loop guidance for micro launchers: Improvement to robustness and failure tolerance

The startup Rocket Factory Augsburg (RFA) is developing the RFA ONE orbital launch vehicle. A significant hurdle for its closed-loop guidance is the need to fully deplete the third stage for insertion during the first flight, which results in lengthy burn-arcs and complexity not managed properly by traditional guidance algorithms. Additionally,...

Interaction-aware Pedestrian Trajectory Prediction using Monocular Video in Automated Driving

Pedestrian trajectory prediction is essential for developing safe autonomous driving systems. Such trajectories depend on various contextual cues, among which surrounding objects. <br/><br/>This work proposes the first pedestrian trajectory prediction method in the 2D on-board domain that models interactions between the pedestrian and...

Vehicle Trajectory Prediction Using Road Structure

An autonomous vehicle should be able to operate amidst numerous other human-driven vehicles, each driving on its own trajectory. To safely navigate in such a dynamic environment, the autonomous vehicle should be able to predict trajectories of the vehicles operating in its vicinity and use these to plan its own path. Most related work uses a...

A Machine Learning Approach to Evaluating Aircraft Deviations from Planned Routes

With the increasing trend in air traffic demand and evidence of large deviations from filed flight plans, airspace capacity is not being optimally utilized. In order to improve air traffic flow and capacity management systems, so that air traffic control operators can handle more aircraft safely, air traffic predictability needs to be improved....

HiPSS-LSTM: A Hierarchical Probabilistic LSTM model for motion forecasting

When driving a car, people can usually predict the intention of other road users with high confidence. They can spot small variations in a recent trajectory, take into account road infrastructure, traffic rules and other factors, which influence a future trajectory. As a result, they can interact with other drivers smoothly and safely. Even...

Sampling-Based MPC with Learning-Based Trajectory Predictions for Interaction-Aware Motion Planning: Autonomous navigation in urban canals

With the world’s population recently surpassing the 8 billion mark, population growth poses significant challenges on the planet. This growth is particularly evident in urban areas, and as a consequence, cities must find innovative ways to accommodate the increasing pressure on the current road infrastructure. In Amsterdam, a city with an...

Machine learning based trajectory prediction to support demand forecasting: A Transformer Neural Network Approach

Air traffic sector demand and capacity balancing is an important process to enable safe and efficient flight execution. In current operations, demand and capacity are determined based on schedules and flight plans. In reality, disruptions to flights create a different situation that may not have been anticipated by the Air Navigation Service...

Smooth-Trajectron++: Augmenting the Trajectron++ behaviour prediction model with smooth attention

Understanding traffic participants’ behaviour is crucial for predicting their future trajectories, enabling autonomous vehicles to better assess the environment and consequently anticipate possible dangerous situations at an early stage. While the integration of cognitive processes and machine learning models has demonstrated promise in various...

Evaluating the impact of prediction accuracy on Continuous Descent Operations: The added value of Trajectory Predictor performance through Air-Ground Datalink

This research investigates the role of time prediction accuracy in optimizing Continuous Descent Operations (CDO) within the aviation sector, with a specific focus on assessing the additional benefits brought forth by the integration of Air-Ground Datalink technologies. Continuous Descent Operations, characterized by uninterrupted and efficient...