BIG DATA ANALYTICS HELP TO REDUCE SEPARATION ON FINAL APPROACH

Optimising runway capacity at Europe’s largest airports will help to accommodate traffic demand and reduce the need to build new infrastructure at already busy airports. One way of optimising runway throughput is by reducing separation between aircraft, using better predicted runway occupancy times.

Runway occupancy times is one most constraining factors to reducing separation, alongside wake turbulence. That is why this solution takes into account local runway occupancy time characterisation (ROCAT) for different aircraft, wake categorisation separation and minimum radar separation (MRS). The solution computes a new separation minimum based on these factors and defines separation sub-categories based on ICAO approved minima.

ROCAT can increase runway throughput by up to 12% where the aircraft traffic mix is predominantly medium aircraft. ROCAT is especially useful where reduced wake separation using the European wake vortex re-categorisation (RECAT-EU) scheme is inefficient due to the lack of wide-body aircraft types in the traffic mix. The solution succeeds in developing runway occupancy minima through big data analytics to identify a runway occupancy time per aircraft type using machine learning techniques and historical data. An air traffic control decision-support tool called optimised runway delivery (ORD) (see solution PJ.02-01-01) enables controllers to deliver a change in the separation minima used by controllers separating aircraft on final approach.

The solution was validated through a real-time simulation in Zurich airport and TMA environments focusing on a range of objectives, such as the operational feasibility, the acceptability of the tool by controllers, safety, human performance and the capacity. It showed that the use of the ORD tool with the ROCAT and a wake vortex pairwise separation scheme (per aircraft type) was operationally feasible and acceptable in segregated runway operations. It also resulted in fewer separation infringements and missed approaches, and controller workload was reduced even though more aircraft were handled by controllers per hour.

The solution is ready for industrialisation and has been implemented in Finland (Helsinki) and the UK (London Heathrow).

BENEFITS

  • Raises capacity by reducing in-trail separation
  • Improves predictability and safety
  • Improved productivity

DATAPACKS

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SESAR2020 Validation of Integrated Runway Sequence Function with AMAN and DMAN

Performed by LFV (COOPANS) in December 2018 and January 2019

runway management PJ02