4D Trajectory Based Operations (TBOs) is a key component of both the US Next Generation Air Transportation System (NextGen) and Europe’s Single European Sky ATM Research (SESAR).
AirTOp supports the modeling of this concept including the modeling of
AirTOp is used by EUROCONTROL and FAA for large scale modelling of traffic covering entire continents or oceans.
Recognised as the State-of-the-Art ATFCM model, where huge data samples can be processed and analysed very quickly, AirTOp is the ideal choice for research projects, for strategic system wide analysis of flow and capacity, or to develop scenarios standard solutions and “playbooks”.
The presentation of performance indicators can be tailored to your needs and easily shared with stakeholders.
AirTOp supports the modeling of planned 4D trajectory being estimated before and during the simulation, as well as being shared by all actors involved in the negotiation of this 4D trajectory (Network/Flow Management actors, ATC actors, AOCs/Aircraft Operators, flight crews).
Planned 4D Trajectories are updated dynamically during simulation in response to controller actions, unexpected delays or DCBMeasures (see below).
Each update of a planned 4D trajectory contains a waypoint profile with norm and planned flyover/flyby times, flyover/flyby altitude, and earliest and latest possible flyover/flyby times. It also contains an airspace profile giving airspace entry/exit times (norm, planned, earliest/latest possible) and entry/exit altitudes.
AirTOp supports the modeling of Network/Flow Management actors using the latest updated planned 4D trajectories to predict any airspace / waypoint or airport demand. Actors can then constantly compare this demand to any limited capacity and negotiate DCB measures if necessary (see below).
The load monitoring tool can dynamically update sector, airspace, waypoint or airport entry and occupancy count ahead of simulation time.
Entry / occupancy count is calculated for different rolling periods in a horizon defined by the user. Entry / occupancy load exceeding given capacity can then be anticipated and assessed by rule conditions. This makes it possible to model and test different strategies to solve the anticipated capacity problems.
Airspace entry count monitoring per rolling user-defined periods ahead of simulation time
Various flow management strategies can be modeled to achieve airspace Demand / Capacity Balancing (DCB):
Airport TMA/TRACON demand/capacity balancing
AirTOp can model different configurations of an AMAN/TMA (Arrival MANager / Traffic Management Advisor).
The AMAN/TMA can anticipate the demand of touch down and build a desired and feasible touch down sequence respecting minimum runway separation (single runway or multiple runways, staggered or not). AirTOp supports the modeling of multiple AMAN/TMA running together on different runway systems.
En-route queuing systems and AMAN/TMA can publish en-route time constraints at different user-defined locations (one or more per flight at waypoint or airspace/sector entry) and with different accuracies (TTA/CTA/RTA)
Strategies to achieve the given target times or separation are user-settable and include
Negotiation between actors can be modeled with user-settable rule bases which determine the chain of actors involved in a negotiation (e.g. the user can choose whether or not to include the tactical controller, planning controller, and aircraft pilot, and in what order).
The duration required to send messages between differenct actors is user settable, as well as the conditions to determine what a Network/Flow Management actor will propose (metering/queueing, airspace re-configuration, re-route, level-capping). Those conditions can be based on the location, duration and severity of the anticipated demand problem. The conditions to determine whether other actors will accept or reject proposals are also user settable (e.g. only accept TTAs below a certain delay threshold, or randomly).
The modeling of negotiation is included in multiple components of the simulation, such as:
Workload associated with negotiation and with flow management can also be simulated dynamically, and can be customized for different actors. The workload model can associate work duration to any event (e.g. different stages of a negotiation, speed change commands issued to meet a TTA, etc). It can take also into account the time spent waiting for a reply from another actor, or the monitoring of flights with any given constraint (TTA, CTA etc). Actor workload can also be measured along specific traffic flows (pairs or sequences of waypoints), and can be customized for different waypoint pairs/sequences.
The work duration associated to event handling can be split into generic user defined activities (radio com, monitoring, conflict resolution etc), and the duration spent per event type and per activity can then be logged per rolling hour.
A customizable event log can be easily created by the user and exported to Excel files or an SQL database for external specific analysis. Events can be related to any action taken by a Network/Flow Management actor (see above) or to any modification of a planned 4D trajectory (TTA publication, achieving/failing to achieve TTA, change of estimated arrival time, re-routing, departure delay, etc). Each event can be logged, together with infomation related to the current status of the aircraft (airline, TTA applied or not, TTA management strategy, amount of delay, etc).
Planned and unplanned delays are measured accurately per flight and can be logged at different times (see above). The difference in flight duration, flight distance, and fuel burn between the last planned 4D trajectory before take off and the final 4D trajectory (updated during flight) can be logged, in absolute terms or as a percentage. Airspace, waypoint or airport entry and occupancy count can be plotted for all types of planned 4D trajectory (initial demand, last plan before take off, final planned trajectory) side by side.