The ORCI project explores new approaches to improve aircraft spacing prediction in arrival operations. By leveraging data-driven techniques, ORCI aims to provide more accurate predictions of the distance between aircraft, supporting more efficient and reliable air traffic management.
Accurate aircraft spacing is essential for safe and efficient operations in busy airspace. Air traffic controllers must continuously manage the sequence of arriving aircraft while ensuring that safe separation is maintained. Predicting how spacing between aircraft will evolve during the arrival phase is therefore a key challenge, especially in complex and dynamic operational environments.
The ORCI project focuses on developing predictive models capable of estimating the future distance between aircraft earlier in the arrival process. By anticipating how spacing will evolve, these predictions can help support improved sequencing decisions and contribute to more stable arrival flows.
To evaluate these approaches in realistic operational environments, ORCI focuses on two specific case studies. The first one is Barcelona, where arrival operations often involve the use of trombone manoeuvres to manage aircraft sequencing. The second case study is Lisbon, where the Point Merge System is used to organise arrival flows. Both procedures are based on RNAV operations, providing suitable operational contexts to analyse spacing evolution and assess the performance of predictive models.
Through collaboration between research and operational partners, the project aims to evaluate these models and explore their potential contribution to future air traffic management tools.
In this news section, we will share updates about the progress of the ORCI project, including technical developments, participation in events, and insights gained throughout the project.
Stay tuned for future updates as ORCI continues to advance research on aircraft spacing prediction. ✈️