Arrival Variability

	Function		Arrival Variability
	Description		This tool permits the user to monitor the actual (real) versus planned differences with respect to flights arriving at one or more airports in a given time period (defaulting to [-2h, 1h] ).
	Access		Workspace > KPIs > Arrival Variability
	Input		Aerodrome(s)		One or multiplean aerodrome ids (separated by a space or a comma)
			(optional) TV		When provided, the KPI will compare arrival times at an airport with the overfly times in a preceding TV (typically the TMA).
			Mode		Variability or Delay
					Many of the KPI tools offer a mode parameter - which can take a value of either VARIABILITY or DELAY. The difference between these 2 values is best explained through an example. Consider, 2 flights – one arriving 5 minutes early and one arriving 5 minutes late. When computing an “arrival KPI” we could either say – • On average, the delay was zero ( (-5 + 5) / 2) • On average, the variability was 5 minutes (i.e. ( |-5| + |5|) / 2) In other words, variability determines the average error in terms of magnitude, ignoring if values are actually –five and +five. Delay on the other hand, does care about the sign of values (-five or +five).
			Past (In min)		With reference to [Go] how may minutes to look in the past
			Future (In min)		With reference to [Go] how may minutes to look forward
			Auto Refresh		never, every 30s, min, 2 min, 3 min, 4 min, 5 min
			Limit Delta Times		The user may specify that “extreme” cases be ignored by specifying a window eliminating all values that are smaller than the minimum and greater than the maximum.
			Graph Filter		Select the source of the traffic: • ALL: All flights, regulated or not • REGULATED: flights subject to a CASA or STAM regulation • NON-REGULATED: flights not subject to a CASA or STAM regulation
			Ignore Non-departed		Toggle to ignore the flights that have not yet departed so only airborne flights are considered.
	Output		The tool will perform a B2B query, obtaining the flights landing at the arrival airport, and the tool will compute the differnece in take off variability versus arrival variability. This will allow to monitor the adherence of flights to their flight plan and/or to the assigned slot times. This graph to allows to investigate systematic early departure, speeding up, and holding.
					A ‘best fit’ trend line is drawn in blue. A reference line at 45 degrees through the origin is also shown in green. So, if the flights, on average, do not speed up/slow down during flight, then the trend line is drawn at a 45 degree angle through the origin.blue trend line is superimposed on the green reference line. If the flights, on average, are delayed during the journey, then the trend-line is above the origin. This KPI panel has also a number of options –    • Non departed flights are ignored    • Limit Delta Times – the user may specify that “extreme” cases be ignored (for example, in the screen shot below, one flight is arriving 70+ minutes late in the sector. If this is considered totally abnormal, the user may limit the delta times to e.g. [-30, +40 min], causing flights outside of this zone to be filtered out from the graphs, and excluded from the statistics). The scatter graph is interactive:    • Flights may be selected (and subsequently viewed on the map)    • The graph may also be zoomed (via the mouse wheel) or panned (via click and drag).