HawkSim Airline
Machine Learning
Hawkrose has developed a machine learning based pre-tactical platform which predicts the risk of ATFM, Turnaround and Local ATC Start Delay at D-1.
- HawkSim Airline generates recommendations for pre-tactical re-routing and where the cost of intervention is too high, recommends that the delay can be absorbed within the block.
- Our system relies on a machine learning based model which has been trained on historical ATFM delay across Europe. All planned lines of flight are assessed for the risk of delay, then the cost of that delay is calculated, and, where cost-effective, alternate routes are proposed.
- There are significant benefits to the pre-emptive replanning of flights in the pre-tactical phase (D-1). Early intervention enables the following: high risk lines of flying to be identified and prioritised, expensive, ineffective re-routings are avoided, decisions being made in a non-pressurised environment, less risk of late-updater flags on a newly filed route, and a more stable schedule, reducing the workload for the flight-ops centre on the day of operation.
- HawkSim Airline was used at D-1 to identify ATC sectors along a line of flying at high risk of delays, the outcome of which created a £20 million annual cost saving for our client.
