ATMRI

Research Projects

Discover some of the research projects at ATMRI

This project aims to develop and design data-driven approaches and machine learning models for airspace and airport optimization with the objective to improve airspace efficiency, en-route congestion, and traffic safety and to optimize ground movements and runway throughput by minimizing taxi delays through accurate taxi-time predictions and arrival departure integration respectively. 

The project aims to build a bundle of machine learning algorithms for air traffic conflicts detection and resolution. These algorithms are expected to make use of historical air traffic data to produce explainable predictive models as parts of a decision support system for air traffic control.

 

This project addresses emerging issues that arise from the creation of safe, beneficial, and trusted AI-ATCO systems for ATM. These issues include AI trust, resilience, safety, transparency, and human performance. To tackle the issues, we investigate and develop practical AI-ATCO teaming frameworks by bringing together principled theories from neuroscience, neuro-inspired AI, and explainable AI. By a better understanding of intelligence from both ATCO and AI aspects, our project can establish confidence in AI-enabled technologies for ATCO.

This project seeks to assess the risk of collision between a manned aircraft and a UAS that is intruding the airport restricted area by evaluating the probability of collision and the severity of the collision on the manned aircraft.
This project seeks to establish separation requirements for the safe operation of UAS whilst minimising inefficiencies and to develop models and methodologies to support conflict management.
This project seeks to facilitate the integration of UAS into airspace so that the airspace is utilised in a safe, efficient, capacity optimised and acceptable manner by determination of the challenges and solutions for the management of UAS traffic and UAM operations – in a global and local (Singapore) context.

This project investigate the operational feasibility of the Free Route Airspace concept in the region. In an initial phase of the study, we quantify the number of potential conflicts as well as the size of their clusters, using a fast-time simulator.

 

Under the LR-ATFM concept, long-range international flights will be assigned Target Time Overs (TTOs) over a waypoint (TTO-fix) well in advance to absorb the delay in the en-route phase of flight, where delay absorption is more efficient compared to terminal delay options. 

We support  regional ASEAN and ICAO working groups in their ATM proposals and benefit analysis
This project seeks to develop a prototype that processes real-time streaming video sequences to detect, track and classify moving objects, in particular, drones.

This project monitors the neuro-visual situation awareness of the ATCO.  The data is captured in real time with the ATCO performing various tactical monitoring tasks and the results analysed.