Sandy Brownlee University of Stirling

2 Outline The ground movement problem Real world data sets OSM / NATS layouts FR24 movements Handling Uncertainty Sources of uncertainty Taxi time uncertainty Possible approaches

3 Ground movement Moving an aircraft from one point to another, in as quick and fuel-efficient way as possible, considering existing aircraft movements and route restrictions

4 Data sets Required? Edge+node coordinates, aircraft timings No substitute for good quality data direct from airports, but freely available: potential for benchmarking OSM – “free to copy, distribute, transmit and adapt our data, as long as you credit OpenStreetMap and its contributors” – so the following are © OpenStreetMap contributors Not perfect – but surprisingly accurate, and can be edited to fix imperfections Export – XML file – taxiways and runways identified by type tags

5 OSM - Manchester

6 OSM - Stansted

7 NATS AIS (Aeronautical information service) Charts and data for UK airports Includes coordinates of stands often missing from OSM

8 Ground movement layouts Used these sources to generate layouts for Birmingham, Edinburgh, Glasgow, Manchester, Stansted – happy to share if they are of use

9 FlightRadar 24 Real-time tracking of ADS-B transponder data Lat/lon/altitude every few seconds Works for most airports in Europe + USA, plus many elsewhere Only includes approx % of flights Somewhat noisy, needs cleaned Can’t be used for example problems, but suitable for analysis of real-world movements Already used in a handful of publications

10 FR24

11 FR24 – actual movements

12 FR24 – actual movements

13 FR24 – stand use rates

14 Approaches to GM Mixture of routing and scheduling Numerous approaches tried, using either fixed routes or shortest paths: Mixed integer linear programming Genetic algorithm Current work is with QPPTW Based on Dijkstra’s algorithm – find quickest path, while respecting times reserved for other aircraft Assumes that times and taxi speed estimates are correct

15 QPPTW at Manchester Demo video

16 Uncertainty Sources of uncertainty Off-block & pushback times Runway times Taxi speeds Runway crossings Breakdowns / blockages Weather Others… Most tend to be handled by simply running the route allocation regularly with most up-to-date data

17 Taxi time uncertainty Taxi times for individual edges are quite variable:

18 Taxi time uncertainty Earlier work (Ravizza 2013, 2014) found taxi time estimates at Zurich to be: Can just add padding but this has an impact on taxi times too (preliminary results follow) Also – variation can be cumulative Estimation accuracy % of movements% of mean taxi time of 443.5s Within 1 min63%13% Within 2 min89%27% Within 3 min97%40%

19 Effect of adding padding Total delay (211 aircraft)

20 Effect of adding padding

21 Handling uncertainty: to-do Improve the modelling further Informed by more real world data Adding buffers to taxi times Better understand the trade-off between buffer size and impact on taxiway capacity A smarter approach to buffering, respecting the distribution of possible taxi times Adopting methods used in job-shop scheduling with uncertain processing times (equating processing time to edge traversal time)

22 Summary Sources for freely-available data: Open street map NATS AIS FlightRadar24 Handling uncertainty in ground movement

23 Thanks Any questions? Useful addresses: