Patent Description:
Landing distance calculations are typically performed by flight crew of an aircraft prior to a landing event on a runway. In some examples, the landing distance calculation accounts for a state of the runway as reported by ground crew, such as received from an air traffic control tower. The state of the runway is reported as, for example, "dry" or "wet". A multiplication factor corresponding to the state of the runway is then used to calculate the landing distance. <CIT> discloses determining an expected braking performance of a second aircraft based on braking information received from a first aircraft that has already landed.

The present disclosure describes a system, specifically an aircraft landing event system, for more accurately determining a performance indicator for an upcoming landing event of an aircraft on a runway. In an example described herein and illustrated in the figures, the performance indicator is a landing distance factor to be applied to a landing distance calculation of the aircraft during the upcoming landing event. The aircraft landing event system is further configured to determine a landing distance on the basis of the landing distance factor, and to communicate the landing distance, and/or the landing distance factor, to a landing system of the aircraft.

Specifically, the aircraft landing event system is configured to consult a database of aircraft landing event data associated with previous landing events of the aircraft approaching the runway and plural other aircraft. The aircraft landing event data includes, for each landing event, environmental conditions of the respective runway - such as a friction of the runway surface and/or a wind speed associated with the landing event - a retardation demand representative of a demand to slow the aircraft on the runway during the landing event, and a performance indicator, such as a landing distance factor, of the aircraft on the runway. In some examples, the retardation demand is determined on the basis of the configuration or type of the aircraft, such as a weight of the aircraft, and whether the aircraft has operable reverse thrusters.

For the upcoming landing event of the approaching aircraft on the runway, the landing event system is configured to determine an environmental condition and a retardation demand. The aircraft landing event system then selects, from the database, aircraft landing event data comprising environmental conditions and retardation demands that are like those of the upcoming landing event. The selected data is used to more accurately determine the performance indicator, such as the landing distance factor, for the upcoming landing. The performance indicator and/or the landing distance determined on the basis thereof is then communicated to a landing system of the aircraft, such as to a braking control system and/or flight deck display.

As will be described herein, to determine the performance indicator, the aircraft landing event data selected from the database is used to determine a relationship between the landing distance factors of previous landing events and the associated environment conditions and retardation demands. That is, the aircraft landing event system uses landing event data of many similar landing events of the current aircraft and plural other aircraft to establish a statistical model - specifically a regression model - representing a variation in the landing distance factor as a function of each of the environmental conditions and retardation demands. The landing distance factor for the upcoming landing event of the approaching aircraft is then determined from the statistical model, by inputting the specific environmental conditions and anticipated retardation demands of the upcoming landing event.

As will also be described herein, in the illustrated example, the aircraft landing event system is configured to determine a performance factor representative of a typical performance of the aircraft compared to other aircraft, on the basis of the selected landing event data. That is, a "bias" of the aircraft compared to the other aircraft is determined. Such a bias may be present due to differences in tyre wear, brake wear, and/or closed loop control tolerances of the aircraft compared to other aircraft, for example. The relationship discussed hereinbefore is then determined on the basis of the performance factor, so that the relationship takes into account the bias of the approaching aircraft. In other words, the landing distance factor is determined by considering the current runway conditions, the anticipated retardation demands, and the typical performance of the aircraft compared to other aircraft. In this way, the relationship provides a more accurate landing distance factor specific to the approaching aircraft.

We now describe an example embodiment of the aircraft landing event system with reference to the Figures.

<FIG> shows a schematic diagram of an example of an aircraft <NUM> comprising a flight deck <NUM> and an aircraft landing event system <NUM>. In the illustrated example, the aircraft <NUM> also comprises an aircraft landing system <NUM>.

<FIG> shows a schematic representation of a runway <NUM> being approached by the aircraft <NUM>. That is, the aircraft <NUM> is approaching the runway <NUM> to perform a landing event on the runway <NUM>, such as in the direction of the arrow in <FIG>. As such, the aircraft <NUM> may be referred to herein as an "approaching aircraft" or "landing aircraft". <FIG> also shows an example of a runway system <NUM> associated with the runway <NUM>. The runway system <NUM> in this example is comprised in an air traffic control tower <NUM> of the runway <NUM>. The aircraft <NUM> is communicatively coupled to the runway system <NUM>. Specifically, the landing event system <NUM> of the aircraft <NUM> is communicatively coupled to the runway system <NUM> via a communications channel or link, which is represented by the dotted line. In some examples, the aircraft landing event system <NUM> and/or the runway system <NUM> comprises a transmitter and/or a receiver, such as comprised in a communications module, for passing information between the aircraft landing event system <NUM> and the runway system <NUM>.

<FIG> shows a schematic diagram of the aircraft landing event system <NUM>. The aircraft landing event system <NUM> comprises a processor <NUM> communicatively coupled, or couplable, with memory <NUM>, which is illustrated in <FIG> as being comprised in the aircraft landing event system <NUM>. The processor <NUM> is also communicatively coupled with the landing system <NUM> of the aircraft <NUM> and the runway system <NUM> of the runway approached by the aircraft <NUM>. The processor <NUM> is configured to send and/or receive signals from the runway system <NUM> and the landing system <NUM>.

The runway system <NUM> is configured to determine an environmental condition of the runway <NUM>. As will be described in more detail hereinafter, the environmental condition is representative of a condition of a surface of the runway <NUM>, and/or an atmosphere surrounding the runway <NUM>. The runway system <NUM> is configured to communicate environment information representative of the environmental condition, such as in the form of an environment signal, to the processor <NUM> of the landing event system <NUM>.

The aircraft landing system <NUM> is configured to determine a retardation demand for an upcoming landing event of the aircraft <NUM> on the runway <NUM>. As will be described in more detail hereinafter, the retardation demand is representative of a demand to slow the approaching aircraft <NUM> on the runway <NUM> during the landing event to a taxiing speed. The aircraft landing system <NUM> is configured to communicate retardation information representative of the retardation demand, such as in the form of a retardation information, to the aircraft landing event system <NUM>, specifically to the processor <NUM>.

The memory <NUM> stores aircraft landing event data. The aircraft landing event data comprises data associated with multiple previous aircraft landing events of the landing aircraft <NUM> and other aircraft. Specifically, the aircraft landing event data comprises landing event data associated with many hundreds, thousands, tens of thousands, or hundreds of thousands of previous landing events of a plurality of aircraft. More specifically, for each landing event, the aircraft landing event data comprises environmental conditions, retardation demands, and performance indicators, such as landing distances or landing distance factors, associated with the respective landing events. In some examples, the memory <NUM> stores aircraft landing event data associated with landing events performed on a plurality of runways, including the runway <NUM> being approached by the landing aircraft <NUM>. In other examples, the landing event data stored in the memory <NUM> is associated with landing events only on the particular runway <NUM> being approached.

The processor <NUM> is configured to receive the environmental information from the runway system <NUM> and the retardation information from the aircraft landing system <NUM>. The processor <NUM> then selects, from the memory <NUM>, aircraft landing event data having environmental conditions and retardation demands corresponding to those represented by the received environmental information and retardation information. That is, the processor <NUM> selects aircraft landing event data of previous landing events that correspond to, or have similar landing profiles to, the upcoming landing event of the approaching aircraft <NUM>.

As will be described in more detail hereinafter in relation to the method <NUM> of <FIG>, in the illustrated example, the processor <NUM> is also configured to determine a performance factor for the aircraft <NUM>, which represents how the aircraft <NUM> typically performs compared to other aircraft used to generate the aircraft landing event data stored in the memory <NUM>.

The processor <NUM> then determines a performance indicator, such as a landing distance factor, for the upcoming landing event, on the basis of the selected data and the performance factor. The performance indicator determined by the processor <NUM> is an anticipated performance indicator of an upcoming landing event of the aircraft <NUM> on the runway <NUM>. In some examples, the performance indicator is any one of the performance indicators described hereinbefore. The processor <NUM> then communicates the landing distance factor to the aircraft landing system <NUM>.

In some examples, the processor <NUM>, or the aircraft landing system <NUM>, is configured to determine a landing distance for the upcoming landing on the basis of the performance indicator. In some such examples, the processor <NUM> is configured to communicate the landing distance to the aircraft landing system <NUM>. In some examples, the aircraft landing system <NUM> comprises a flight deck element, such as a flight deck display, and is configured to communicate the performance indicator and/or the determined landing distance to the flight deck element, such as to display the performance indicator and/or landing distance on the flight deck display.

In examples comprising a flight deck element, flight crew of the aircraft <NUM> are provided with an indication of, and/or an opportunity to take action on the basis of, the performance indicator and/or the landing distance associated with the upcoming landing event of the aircraft <NUM> on the runway <NUM>. For example, if the determined landing distance is less than that expected, such as less than a landing distance calculated using predetermined conservative multiplication factors, the flight crew may decide to cause the aircraft <NUM> to touchdown later on the runway <NUM>. This may reduce fuel burn and/or noise pollution of the landing aircraft <NUM>. Alternatively, if the anticipated landing distance is larger than expected, given the environmental conditions of the runway, the achievable retardation demand from the aircraft <NUM>, and the typical performance of the aircraft <NUM> compared to other aircraft, the flight crew may decide to land the aircraft <NUM> on a different runway to the runway <NUM>, such as an adjacent runway, or even a runway at another airport. In some examples, the aircraft <NUM> comprises an autopilot system (not shown), which can make such decisions on behalf of flight crew. In such examples, the processor <NUM> and/or the aircraft landing system <NUM> may be configured to communicate the performance indicator and/or the determined landing distance to the autopilot system.

We now describe, in more detail, examples of the types of environmental conditions, retardation demands, and aircraft landing event data that can be used by the processor <NUM>. We then describe, with reference to the method shown in <FIG>, how these conditions and demands may be used by the processor <NUM> to determine the performance indicator, in the illustrated example presented herein.

In some examples, the environment condition comprises an atmospheric condition associated with the runway <NUM>, such as any one or more of: a wind speed; a wind direction; a temperature; a level of precipitation; and a humidity. In some examples, the environment condition comprises a surface condition of the runway <NUM>, such as any one or more of: a friction; a surface coating (e.g. a level of "wetness", or a category such as wet/dry/icy/oil-coated); and a runway material. In some examples, the environment condition comprises a runway identifier for identifying the runway <NUM>.

In some examples, the environment condition comprises a parameter representative of a wheel slip measured by a braking system of an aircraft which has recently landed on the runway <NUM>. The term "wheel slip" is understood to represent a level of reactive force able to be developed between a wheel of an aircraft and a runway before the wheel locks and starts to slide over the runway surface without rotating. This, in turn, is representative of a friction of the runway. For example, a surface coating of water on the runway, such as the runway <NUM>, may lower the coefficient of friction of the runway <NUM>. This, in turn, may cause the wheel to lock at a lower reactive force, and thus with a lower braking applied by the braking system, than if the runway <NUM> were dry.

In some examples, an anti-lock braking system is configured to cause braking of the wheels of such an aircraft to maximise wheel slip. That is, the anti-lock braking system causes the level of braking to be maintained at a level close to, but not exceeding, a level that would cause the wheel to lock. In some examples, for a landing event of a previously-landed aircraft, an anti-lock braking system of that aircraft determines the parameter representative of the maximum achieved wheel slip in the form of a braking force, or braking torque, able to be output by a braking system of the aircraft before one or more wheels lock. In some examples, the approaching aircraft <NUM> comprises such an anti-lock braking system.

In some examples, the environment condition is provided in the form of a profile of a condition of the runway <NUM> over a length of the runway <NUM>, and/or a mapping of the condition of the runway <NUM> over a length and a breadth of the runway <NUM>. For example, the environment condition may be a maximum wheel slip profile representing a maximum level of wheel slip achieved by a respective aircraft as a function of a distance of the aircraft along the runway <NUM>.

In some examples, the retardation demand comprises any one or more of: a deceleration demand; a brake demand (e.g. brake force); a thrust reverser demand; a landing speed; and a configuration of the aircraft, such as the presence or absence of operable thrust reversers, and/or an extension of flight surfaces of the aircraft, such as slats, flaps and/or spoilers. In some examples, the retardation demand is provided in the form of a profile of a demand to slow the aircraft <NUM> over a length of the runway <NUM>, and/or a mapping of a demand to slow the aircraft <NUM> over a length and a breadth of the runway <NUM>.

In some examples, the retardation demand is determined on the basis of an input from flight crew and/or an autopilot of the approaching aircraft <NUM>, such as an input representing a desire to slow the aircraft <NUM> to a taxiing speed on the runway <NUM>. In some examples, the retardation demand is determined on the basis of any one or more of: a weight of the approaching aircraft <NUM>; a brake capacity of the approaching aircraft <NUM>; an available length of the runway <NUM> on which the aircraft can perform a landing event; and a speed of the aircraft <NUM>, such as a flight speed and/or an anticipated speed of the aircraft <NUM> during touchdown of the aircraft <NUM> on the runway. In some examples, the estimated retardation demand is also based on the condition of the runway <NUM>, such as that represented by the received environment information.

In other words, the retardation demand is a reasonable estimate of the retardation functions required to slow the approaching aircraft <NUM> on the runway <NUM>, based on a current state of the aircraft <NUM>, and, in some examples, a current state of the runway <NUM>. This initial estimate may be sub-optimal, in that conservative assumptions may be made about the performance of the aircraft <NUM> and/or the condition of the runway <NUM> when determining the retardation demand. By determining the performance indicator as described herein, a more accurate landing distance of the aircraft <NUM> may be determined, and the anticipated retardation demand may be adjusted accordingly. This may be iterative, in order to provide a better estimate of the retardation demand and/or the landing distance for the upcoming landing event.

In some examples, the aircraft <NUM> comprises one or more sensors and/or systems (not shown) for detecting a current status of the aircraft <NUM>. In some examples, the current status comprises one or more of: a location of the aircraft <NUM>; an attitude of the aircraft <NUM>; an inertial reference of the aircraft <NUM>, such as an airspeed, angle of attack and/or altitude of the aircraft <NUM>; a mass, or weight, of the aircraft; a centre of gravity the aircraft; and a configuration of the aircraft <NUM>, such as a configuration of a landing gear and/or flight surface of the aircraft <NUM>. In some examples, the one or more sensors and/or systems comprises any one or more of: a Global Positioning System (GPS); an accelerometer; an airspeed sensor; a fuel level sensor; and an altitude sensor. In some examples, the status of the aircraft <NUM>, as detected by the sensors, is used to determine one or more of the environmental conditions and/or retardation demands of the upcoming landing event. By way of an illustrative example only, a fuel level sensor may be used to determine a current mass and/or a centre of gravity of the aircraft. The mass and/or centre of gravity may then be used to determine a retardation demand of the aircraft, such as to determine a required flight surface configuration for touchdown and/or to estimate a downforce on a particular wheel or landing gear of the aircraft during the upcoming landing event. In some examples, the sensors are configured to directly sense an environment condition, such as an atmospheric condition as described hereinbefore. In some examples, the aircraft landing system <NUM> is configured to receive environment information representative of the environment condition sensed by the sensors, and to communicate the environment information to the processor <NUM>.

In some examples, the performance indicator for the upcoming landing event and/or for each landing event of the aircraft landing event data stored in the memory <NUM>, is, or is representative of, any one of: a landing distance factor for the respective landing event; a landing distance of the respective landing event; and a time to slow the respective aircraft from a landing speed to a predetermined threshold speed. It will be understood that the performance indicator can be defined in any other suitable way.

In some examples, the "landing distance" referred to herein is a distance travelled by a respective aircraft from touchdown of the aircraft on a runway until a speed of the aircraft drops below a predetermined threshold speed, such as until the aircraft reaches a taxiing speed. In some examples the predetermined threshold speed is zero, such that the landing distance is a distance over which the aircraft is slowed to a stop following touchdown of the aircraft on a runway. In other examples, the landing distance is a distance from touchdown of the aircraft on the runway to location where the aircraft merges onto a taxiway branching from the runway.

Turning now to <FIG>, we describe a method <NUM> of determining the performance indicator of the landing aircraft <NUM>. The method <NUM> is performed by the landing event system <NUM>, specifically the processor <NUM>. As such, the method <NUM> is herein described in relation to actions the processor <NUM> is configured to perform. It will be understood, however, that in other examples the method <NUM> is performed by any other suitable processor and/or system.

As noted hereinbefore, the landing event system <NUM>, and specifically the processor <NUM>, is configured to receive <NUM> the environment information from the runway system <NUM>, and to receive <NUM> the retardation information from the aircraft landing system <NUM> as described hereinbefore. The processor <NUM> is also configured to: select <NUM> aircraft landing event data from the memory <NUM> on the basis of the received <NUM>, <NUM> environment information and retardation information; determine <NUM> a performance indicator of the landing aircraft <NUM> on the basis of the aircraft landing event data selected <NUM> by the processor <NUM>; and communicate <NUM> the performance indicator to the landing system <NUM>. In the illustrated example, the performance indicator is a landing distance factor to be applied to a landing distance calculation, as described hereinbefore.

In some examples it will be understood that the receiving <NUM> the environment information by the processor <NUM> comprises determining <NUM> one or more environmental conditions, such as on the basis of the received environment information. Similarly, it will be understood that, in some examples, the receiving <NUM> the retardation information by the processor <NUM> comprises determining <NUM> one or more retardation conditions, such as on the basis of the received retardation information.

That is, in the illustrated example, the processor <NUM> is configured to select <NUM>, or extract, aircraft landing event data having environmental conditions and retardation demands that correspond to, or are broadly similar to, the environmental conditions and retardation demands of the upcoming landing event of the landing aircraft <NUM> on the runway <NUM>. Specifically, in the illustrated example, the method <NUM> comprises selecting <NUM>, from the memory <NUM>, aircraft landing event data comprising environmental conditions and retardation demands that are within a predetermined range of, respectively, the environmental condition and retardation demand represented by the received environment information and retardation information. In other words, the method comprises selecting <NUM> only the aircraft landing event data that is that relevant to the upcoming landing event.

In some examples, to select <NUM> the aircraft landing event data, the processor <NUM> is configured to select <NUM>, from the memory <NUM>, aircraft landing event data associated only with the runway <NUM> being approached by the aircraft. In other examples, the aircraft landing event data selected <NUM> by the processor <NUM> may be aircraft landing event data from any suitable runway.

In some examples, the processor <NUM> is configured to select <NUM> aircraft landing event data comprising environmental conditions and/or retardation demands that are within up to <NUM>%, up to <NUM>%, up to <NUM>%, up to <NUM>%, up to <NUM>%, or greater than <NUM>% of, respectively, the environmental conditions and retardation demands represented by the environment information and retardation information. In an illustrative example, for ease of understanding, the environment information is representative of environmental conditions comprising a crosswind having a speed of <NUM> knots, and a runway surface classified as "wet". The retardation information is representative of retardation demands comprising a demand to brake the aircraft <NUM> by employing reverse thrusters at <NUM>%, and a demand to apply <NUM>% more braking force to wheels on a first side of a fuselage of the aircraft <NUM> than wheels on a second, opposite side of the fuselage. That is, the crosswind may increase a downforce on the first-side wheels, allowing them to be braked with a higher braking force. In that case, the processor <NUM> selects <NUM> aircraft landing event data from the memory <NUM> comprising: a crosswind of between <NUM> knots and <NUM> knots; a runway surface condition in the category "wet"; reverse thruster demands of between <NUM>% and <NUM>%; and brake demands of wheels on the first side of the aircraft fuselage of between <NUM>% and <NUM>% more than brake demands for wheels on the second side of the aircraft fuselage. It is reiterated that this is an illustrative example only, and that the aircraft landing event data may be matched to any other suitable environment conditions and/or retardation demands.

As stated hereinbefore, in some examples, the memory <NUM> is configured store aircraft landing event data of many hundreds of thousands (or more) of aircraft landing events. As such, in some examples, in order to select <NUM> the aircraft landing event data from the memory <NUM>, the processor <NUM> is configured to implement a machine learning technique or other advanced data analytic technique. In other words, the landing event system <NUM> uses artificial intelligence to select <NUM> the aircraft landing event data from the memory <NUM>. In some examples, the processor <NUM> is configured to use a neural network system trained to select <NUM> suitable aircraft landing event data from the memory on the basis of the environmental and retardation information. In such examples, the neural network is regularly updated and trained to account for new aircraft landing event data stored in the memory <NUM>. In some examples, the processor is configured to select the aircraft landing event data in any other suitable way, such as by using any suitable data selection and/or matching method. That is, the aircraft landing event data may, in some examples, be selected without using a machine learning and/or artificial intelligence technique.

In the illustrated example, to select <NUM> the aircraft landing event data, the processor <NUM> is configured to select <NUM>, from the memory <NUM>, aircraft landing event data of both the landing aircraft <NUM> and other aircraft on the basis of the environment information and the retardation information. To determine <NUM> the performance indicator, the processor <NUM> is configured to compare <NUM> the landing event data of the landing aircraft <NUM> with the landing event data of the other aircraft, as selected by the processor <NUM>. Specifically, the comparing <NUM> comprises determining <NUM> a performance factor representative of a performance of the landing aircraft <NUM> compared to the other aircraft.

In the illustrated example, to determine <NUM> the performance factor, the processor <NUM> is configured to determine, from the aircraft landing event data, a statistical distribution of recorded landing distances for the landing events of aircraft other than the landing aircraft <NUM>. <FIG> shows an example such a distribution <NUM> represented by a distribution curve <NUM>, which here is a bell curve resembling a normal distribution. Specifically, the distribution curve <NUM> shows a frequency (on the y-axis) at which the landing distances (on the x-axis) occur in the aircraft landing event data selected by the processor. It will be understood that the statistical distribution <NUM> of landing distances is provided for environmental conditions and/or retardation demands which are the same or broadly similar to those of the upcoming landing event of the landing aircraft <NUM>. In other examples, the statistical distribution is a statistical distribution of landing distance factors, or other suitable aircraft landing performance indicators.

To determine <NUM> the performance factor, the processor <NUM> is configured to determine an average landing distance <NUM>, such as a mean or a median landing distance <NUM>, on the basis of the distribution <NUM>. <FIG> shows a dashed line numbered <NUM> indicating such a median landing distance <NUM>, which represents the typical performance of a "median aircraft" for the environmental conditions and retardation demands of the upcoming landing event of the landing aircraft <NUM>. The processor <NUM> is then configured to determine a landing distance <NUM>, or average landing distance <NUM>, such as a mean or median landing distance <NUM>, of the landing aircraft <NUM>. Specifically, the average landing distance <NUM> of the landing aircraft <NUM> is determined based on aircraft landing event data of previous landing events of the landing aircraft <NUM> under similar environmental conditions and retardation demands to those of the upcoming landing event.

The processor <NUM> is then configured to compare <NUM> the average landing distance <NUM> of the landing aircraft <NUM> with the average landing distance <NUM> of the "median aircraft". In the illustrated example, the comparing <NUM> is performed by determining <NUM> the performance factor on the basis of the average landing distances of both the landing aircraft <NUM> and the median aircraft. Specifically, the processor <NUM> is configured to determine <NUM> the performance factor as a ratio, or difference, between the average landing distance <NUM> of the landing aircraft <NUM> and the average landing distance <NUM> of the median aircraft. In other examples, the performance factor is represented as a standard deviation of the average landing distance <NUM> of the landing aircraft <NUM> from the average landing distance <NUM> of the median aircraft. The performance factor is then stored in the memory <NUM>, along with the associated environmental conditions and retardation demands. In some examples, the performance factor is passed to flight crew and/or maintenance crew. In this way, if the performance factor indicates that the aircraft is performing sub-optimally, this may be flagged to the flight crew and/or the maintenance crew, and an investigation and/or maintenance procedure may be initiated.

It will be understood that the performance factor represents a typical performance of the landing aircraft <NUM> compared to that of the median aircraft. In other words, the performance factor is indicative of a "bias" of the landing aircraft <NUM> compared to other aircraft. In the example shown in <FIG>, the average landing distance <NUM> of the landing aircraft <NUM> is larger than the average landing distance <NUM> of the median aircraft, which may indicate, for example, that the landing aircraft <NUM> typically exhibits a lower braking performance than other, similar aircraft under similar landing conditions. This may be due to, for example, differences in tyre wear, brake wear, aerodynamic performance, equipment tolerances, and/or closed loop control tolerances of the landing aircraft <NUM> compared to the other aircraft.

It will also be understood that as components of the landing aircraft <NUM>, such as tyres, brake pads and other braking system components, degrade through use, the average landing distance <NUM> of the landing aircraft <NUM> may move further to the right in <FIG> (i.e. the typical landing distance of the landing aircraft <NUM> may increase). In some examples, the average landing distance <NUM> of the landing aircraft <NUM> may be a weighted average landing distance <NUM>, weighted towards more recent landing events. In this way, the average landing distance <NUM> may provide a more up-to-date representation of the current state of the landing aircraft <NUM>. For example, a newer landing aircraft <NUM>, or a landing aircraft <NUM> that has recently received replacement braking system components, such as new tyres and/or brake pads, may perform better than the median aircraft. In such a case, an average landing distance <NUM> of the landing aircraft <NUM> may be less than the average landing distance <NUM> of the median aircraft.

As will be discussed in more detail below, in other examples, the processor <NUM> may not determine <NUM> the performance factor, or may determine <NUM> the performance factor to be a predetermined conservative multiplication factor. Using a predetermined conservative multiplication factor may equate to using a conservative average landing distance for the landing aircraft <NUM>, as illustrated by the line <NUM> in <FIG>.

Returning now to <FIG>, in the illustrated example, to determine <NUM> the performance indicator of the landing aircraft, the method <NUM> further comprises determining <NUM>, on the basis of the aircraft landing event data selected <NUM> by the processor <NUM>, a relationship between the performance indicators of the selected aircraft landing event data and one or a number of the stored environmental conditions and retardation demands. The processor <NUM> then determines <NUM> the performance indicator of the landing aircraft <NUM> on the basis of the relationship and the received environment information and the retardation information.

To determine <NUM> the relationship, the processor <NUM> is configured to perform a statistical analysis on the selected <NUM> aircraft landing event data. Specifically, in the present example, the processor <NUM> is configured to determine a regression model of the relationship between the performance indicators of the selected <NUM> aircraft landing event data (herein the "selected performance indicators") and each of the environmental conditions and retardation demands which have been used to select <NUM> the aircraft landing event data.

<FIG> shows an example of such a relationship 700a between the selected <NUM> performance indicators and an environmental condition. In <FIG>, for ease of understanding, the selected <NUM> performance indicators are landing distance factors of the landing events from which the aircraft landing event data is compiled, and the environmental condition is a runway surface wetness. <FIG> shows another example of such a relationship 700b, this time between the stored performance indicators and a retardation demand, such as a total braking force of all wheels of an aircraft. <FIG> show respective sets of data points 710a, 710b of the selected <NUM> aircraft landing event data. <FIG> also show respective regression curves 720a, 720b determined <NUM> by the processor <NUM> based on the respective sets of data points 710a, 710b, in the illustrated example.

It can be seen that the relationship 700a, 700b for each of the environmental conditions and/or retardation demands is defined over a range of the respective environmental conditions and/or retardation demands. The range in each case is relatively narrow, as a result of the processor <NUM> selecting <NUM> aircraft landing event data having environmental conditions and retardation demands that are similar to, such as within a particular range of, those represented by the received <NUM>, <NUM> environment information and retardation information, as discussed hereinbefore.

In the illustrated example, the processor <NUM> is configured to account for the performance factor when determining <NUM> the relationships between the selected <NUM> performance indicators, environmental conditions and retardation demands. Specifically, the performance factor is used to generate an adjusted regression model, which is represented by the regression curves numbered 730a and 730b in respective <FIG>. In this way, by taking into account the bias of the landing aircraft <NUM> compared to other aircraft, the adjusted regression curves 730a, 730b represent relationships between the landing distance factor and both the environment conditions and retardation demands for the specific landing aircraft <NUM>.

The processor <NUM> is then configured to determine <NUM> the performance indicator for the upcoming landing on the basis of the regression models 700a, 700b, the environmental conditions and the retardation demands for the upcoming landing. Specifically, for the given environment condition and retardation demand of the upcoming landing event (e.g. for a particular surface wetness of the runway <NUM> and anticipated braking force demand), the processor <NUM> determines the landing distance factors from the adjusted regression curves 730a, 730b. The processor <NUM> then uses these landing distance factors to determine a total landing distance factor, such as by taking an average, weighted average, or other suitable statistical measure of the determined landing distance factors.

In the illustrated example, the method <NUM> also comprises determining <NUM> a landing distance for the upcoming landing event of the landing aircraft <NUM> on the basis of the performance indicator. Specifically, the landing distance is determined <NUM> by applying the determined <NUM> performance indicator, such as in the form of a multiplication factor, to a typical landing distance calculation based on the environmental conditions and retardation demands for the upcoming landing event. In examples where such a landing distance is determined <NUM>, the communicating <NUM> the performance indicator to the landing system <NUM> of the landing aircraft <NUM> instead, or in addition, comprises communicating <NUM> the landing distance to the landing system <NUM>.

In some examples, the performance indicator for the upcoming landing event is instead determined <NUM> using the unadjusted relationships 720a, 720b, without taking into account the performance factor, and the performance factor is subsequently applied as a multiplication factor when determining <NUM> the landing distance. In some examples, the performance factor is a pre-determined conservative performance factor, as discussed hereinbefore, leading to a conservative performance indicator and/or landing distance. In other examples, the method <NUM> does not comprise determining <NUM> the performance factor, and instead comprises determining <NUM> the performance parameter <NUM> (and subsequently determining <NUM> the landing distance) on the basis of the unadjusted regression models 720a, 720b alone. In this case, the determined <NUM> landing distance for the upcoming landing event may be more realistic than one calculated using a conservative multiplication factor, but may be less accurate than if the calculation were to take into account the bias of the landing aircraft <NUM>.

It will be understood that the bias of the landing aircraft <NUM>, and/or the determined <NUM> relationship, or regression model, may be determined more accurately by providing a larger dataset from which to select <NUM> the aircraft landing event data of the landing aircraft <NUM> and other aircraft. As such, the aircraft landing event data stored in the memory <NUM> should be built up over time to provide aircraft landing event data for landing events of the landing aircraft <NUM> and other aircraft on many different runways, and under many different environmental conditions and retardation demands.

<FIG> shows a schematic diagram of a non-transitory computer-readable storage medium <NUM> according to an example. The non-transitory computer-readable storage medium <NUM> stores instructions <NUM> that, if executed by a processor <NUM> of a controller <NUM> or system <NUM>, cause the processor <NUM> to perform a method according to an example. In some examples, the controller <NUM> or system <NUM> is the landing event system <NUM> and the processor <NUM> is the processor <NUM> as described above with reference to <FIG> or any variation thereof discussed herein.

The instructions <NUM> comprise: receiving <NUM> environment information representative of an environmental condition; receiving <NUM> retardation information representative of a retardation demand; selecting <NUM>, on the basis of the environmental information and the retardation information, aircraft landing event data from a memory, such as the memory <NUM>; determining <NUM> a performance indicator on the basis of the selected <NUM> aircraft landing event data; and communicating <NUM> the performance indicator, or information representative thereof, to the landing system <NUM> of the landing aircraft <NUM>. In other examples, the instructions <NUM> comprise instructions to perform any other example method described herein, such as the method <NUM> described above with reference to <FIG>.

It will be understood that while the above examples are described in relation to an aircraft landing event system <NUM> of an aircraft <NUM>, in some examples, the aircraft landing event system <NUM> is comprised in an air traffic control tower <NUM> of a runway <NUM>, or in any other suitable location. Moreover, although the aircraft landing event system <NUM> described herein is communicatively coupled to the landing system <NUM> of the aircraft <NUM> and the runway system <NUM>, in other examples, the aircraft landing event system comprises either or both of the landing event system <NUM> and the runway system <NUM>. In other examples, the aircraft landing system <NUM> is configured to be communicatively coupled, or couplable, to the runway system <NUM>. In this way, the processor <NUM> may be configured to receive environment information from the landing system <NUM> rather than, or as well as, from the runway system <NUM>.

In some examples, the memory <NUM> is a cloud-based memory <NUM>, such as accessible via a networked communication system. In other examples, the memory <NUM> is comprised in the aircraft landing event system <NUM>, the runway system <NUM>, or the aircraft landing system <NUM>. In some examples, the runway system <NUM> and/or the aircraft landing system <NUM> is communicatively coupled, or couplable, to the memory <NUM> or a part of the memory.

In some examples, the processor <NUM> is configured to cause one or more of: the environment condition(s) of the runway <NUM>; the retardation demand(s) of the landing aircraft <NUM>; the relationship(s); and the performance factor(s), to be stored in the memory <NUM>, or any other suitable memory, such as before, during, or after the upcoming landing event of the landing aircraft <NUM> on the runway <NUM>.

Claim 1:
An aircraft landing event system (<NUM>) comprising a processor (<NUM>)
communicatively coupled with memory (<NUM>) storing previous aircraft landing event data,
the processor configured to:
receive environment information representative of an environmental condition of a runway (<NUM>) approached by an aircraft (<NUM>);
receive, from a landing system of the aircraft, retardation information representative of a retardation demand of the aircraft during an anticipated landing event of the aircraft on the runway, wherein the retardation demand is determined by the landing system of the aircraft;
select aircraft landing event data from the memory on the basis of the environment information and the retardation information;
determine a performance indicator for the landing event on the basis of the aircraft landing event data selected by the processor; and
communicate the performance indicator to the landing system (<NUM>) of the aircraft;
wherein the processor is configured to determine a relationship between performance indicators and both environment conditions and retardation demands of the aircraft landing event data selected by the processor, and
wherein the processor is configured to determine the performance indicator for the anticipated landing event on the basis of the relationship.