U.S. patent application number 16/806562 was filed with the patent office on 2020-06-25 for aircraft braking based on real time runway condition.
The applicant listed for this patent is AIRBUS GROUP INDIA PRIVATE LIMITED. Invention is credited to Anurag Sharma.
Application Number | 20200198604 16/806562 |
Document ID | / |
Family ID | 58799777 |
Filed Date | 2020-06-25 |
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United States Patent
Application |
20200198604 |
Kind Code |
A1 |
Sharma; Anurag |
June 25, 2020 |
AIRCRAFT BRAKING BASED ON REAL TIME RUNWAY CONDITION
Abstract
Disclosed is an example for performing aircraft braking based on
real time runway condition. In one example, during landing, real
time data of runway condition may be obtained using at least one
sensor disposed around an aircraft. At least one brake factor may
be determined based on the real time data of the runway condition.
Aircraft braking may be controlled based on the at least one brake
factor.
Inventors: |
Sharma; Anurag; (Bangalore,
IN) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
AIRBUS GROUP INDIA PRIVATE LIMITED |
Bangalore |
|
IN |
|
|
Family ID: |
58799777 |
Appl. No.: |
16/806562 |
Filed: |
March 2, 2020 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
15369918 |
Dec 6, 2016 |
10576948 |
|
|
16806562 |
|
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
B64C 25/42 20130101;
B60T 2210/12 20130101; B60T 8/1703 20130101; B60T 8/172
20130101 |
International
Class: |
B60T 8/17 20060101
B60T008/17; B64C 25/42 20060101 B64C025/42; B60T 8/172 20060101
B60T008/172 |
Foreign Application Data
Date |
Code |
Application Number |
Dec 8, 2015 |
IN |
6570CHE2015 |
Claims
1. A braking control system for an aircraft comprising: at least
one sensor; one or more processor in communication with the at
least one sensor, the one or more processor configured to: receive
data indicating a condition of one or more runway segment of a
runway from the at least one sensor; and determine a braking
performance of the aircraft for the one or more runway segment; and
a braking controller configured to control braking of the aircraft
on the runway according to the determined braking performance when
an undercarriage or landing mechanism of the aircraft encounters
the one or more runway segment.
2. The system of claim 1, wherein the at least one sensor is
attached to the aircraft and configured to capture the data as
real-time data of images of the runway in front of the aircraft as
the aircraft is landing.
3. The system of claim 1, further comprising a database having at
least a look-up table comprising a set of reference spectral bands
and intensities corresponding to a known contaminant set; wherein
the determined braking performance is based on the condition of the
one or more runway segment; and wherein the condition of the one or
more runway segment corresponds to a presence or absence of one or
more contaminants on a surface of the one or more runway
segment.
4. The system of claim 3, wherein the one or more contaminants on
the surface of the runway comprises one or more of visible or
non-visible moisture, ice, slush, brine, gravel, rocks, debris,
salt, oil, fuel, or snow.
5. The system of claim 3, wherein the received data indicating the
condition of the one or more runway segment comprises images of the
runway in front of the aircraft as the aircraft is landing; wherein
each image is associated with a corresponding segment of the one or
more runway segment; wherein the one or more processor is further
configured to: extract feature data from the images, wherein the
feature data comprises sensed spectral bands and intensities that
correspond to a captured runway image within a field-of-view of the
sensor; detect a presence or absence of at least one contaminant on
each of the one or more runway segment by comparing sensed spectral
bands and intensities with the set of reference spectral bands and
intensities; determine a depth of the contaminants on each runway
sub-region; generate a map of each of the one or more runway
segment with contaminant patches in a direction of motion of the
aircraft based on the determined contaminants and the depth of the
contaminants; and determine, using the map, the contaminated
patches corresponding to each of the one or more runway segments
that is determined to be in a landing path of the aircraft.
6. The system of claim 5, wherein the one or more processor is
further configured to: correlate the determined contaminated
patches in the landing path of the aircraft with pre-stored runway
conditions in the look-up table; and determine the at least one
braking performance corresponding to each of the one or more runway
segment that is in the landing path of the aircraft from a set of
pre-stored braking performances based on the correlation, wherein
the set of pre-stored braking performances correspond to different
runway conditions and are stored in the look-up table.
7. The system of claim 6, wherein the pre-stored runway conditions
comprise one or more of: a runway surface material; elements or
compositions of the contaminants on a surface of the runway;
category of contaminants; an extent of a coverage or area of the
contaminants; segment-wise distribution of contaminants on the
surface of the runway; and depth of contaminants present on the
surface of the runway.
8. The system of claim 6, wherein the braking control unit is
configured to control aircraft braking by using braking
performances associated with each of the one or more runway segment
when the aircraft encounters a corresponding physical runway
segment upon touch-down of the aircraft.
9. The system of claim 1, wherein the one or more sensor comprises
an imaging device.
10. The system of claim 9, wherein the imaging device comprises a
hyperspectral camera or a multispectral camera, each having a
field-of-view within which the runway in front of the aircraft can
be captured.
11. A method for braking of an aircraft comprising: receiving, at
one or more processor, data indicating a condition of one or more
runway segment of a runway from at least one sensor; determining a
braking performance of the aircraft for the one or more runway
segment; and braking the aircraft according to the braking
performance when an undercarriage or landing mechanism of the
aircraft encounters the one or more runway segment.
12. The method of claim 11, wherein the at least one sensor is
attached to the aircraft and the method further comprises capturing
the data as real-time data of images of the runway in front of the
aircraft as the aircraft is landing.
13. The method of claim 11, further comprising: providing a
database having at least a look-up table comprising a set of
reference spectral bands and intensities corresponding to a known
contaminant set; and wherein the braking performance is based on
the condition of the one or more runway segment; wherein the
condition of the one or more runway segment corresponds to a
presence or absence of one or more contaminants on a surface of the
one or more runway segment.
14. The method of claim 13, wherein the one or more contaminants on
the surface of the runway comprises one or more of visible or
non-visible moisture, ice, slush, brine, gravel, rocks, debris,
salt, oil, fuel, or snow.
15. The method of claim 13, wherein the received data indicating
the condition of the one or more runway segment comprises images of
the runway in front of the aircraft as the aircraft is landing;
wherein each image is associated with a corresponding segment of
the one or more runway segment; the method further comprising, at
the one or more processor: extracting feature data from the images,
wherein the feature data comprises sensed spectral bands and
intensities that correspond to a captured runway image within a
field-of-view of the sensor; detecting a presence or absence of at
least one contaminant on each of the one or more runway segment by
comparing sensed spectral bands and intensities with the set of
reference spectral bands and intensities; determining a depth of
the contaminants on each runway sub-region; generating a map of
each runway segment with contaminant patches in a direction of
motion of the aircraft based on the determined contaminants and the
depth of the contaminants; and using the map to determine the
contaminated patches corresponding to each of the one or more
runway segments that is determined to be in a landing path of the
aircraft.
16. The method of claim 15, further comprising, at the one or more
processor: correlating the determined contaminated patches in the
landing path of the aircraft with pre-stored runway conditions in
the look-up table; and determining the at least one braking
performance corresponding to each of the one or more runway segment
that is in the landing path of the aircraft from a set of
pre-stored braking performances based on the correlation, wherein
the set of pre-stored braking performances correspond to different
runway conditions and are stored in the look-up table.
17. The method of claim 16, wherein the pre-stored runway
conditions comprise one or more of the following: a runway surface
material; elements or compositions of the contaminants on a surface
of the runway; category of contaminants; an extent of a coverage or
area of the contaminants; segment-wise distribution of contaminants
on the surface of the runway; and depth of contaminants present on
the surface of the runway.
18. The method of claim 16, further comprising using brake
performances associated with each of the one or more runway segment
to brake the aircraft consistent with the braking performance when
the aircraft encounters a corresponding physical runway segment
upon touch-down of the aircraft.
19. The method of claim 11, wherein the one or more sensor
comprises an imaging device.
20. The method of claim 19, wherein the imaging device comprises a
hyperspectral camera or a multispectral camera, each having a
field-of-view within which the runway in front of the aircraft can
be captured.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application is a continuation of and claims priority to
U.S. patent application Ser. No. 15/369,918 filed Dec. 6, 2016,
which claims the benefit of and priority to Indian Application
Serial No. 6570/CHE/2015 filed Dec. 8, 2015, the entire disclosures
of which are herein incorporated by reference.
TECHNICAL FIELD
[0002] Embodiments of the present subject matter generally relate
to aircrafts, and more particularly, to aircraft braking based on
real time runway condition.
BACKGROUND
[0003] Runways are commonly used for an aircraft to travel during
takeoff and during landing. During landing, runway
conditions/braking assessment may be received from air traffic
controllers for aircraft braking. Conditions that develop on
runways may vary with weather and other phenomenon. For example,
conditions that develop on the runways may include, without
limitation, snow, standing water, slush, ice, debris, indentations,
and plant growth that extend onto the runway.
[0004] Conditions for a runway may be noted by pilots of aircraft
that are using the runway or by equipment at airport/air traffic
controllers or braking performance may be reported by the landing
aircraft to an airport. The pilots or equipment operators may
communicate the conditions for the runway to the air traffic
controllers. Further, the air traffic controllers may inform other
aircrafts of the conditions. In some cases, the runway conditions
available with the air traffic controllers may be out-dated or
irrelevant to the aircraft weight category (e.g., wheel tyre
loading). For example, the braking assessment/runway condition data
from the air traffic controllers to an aircraft may not be possible
or accurate when the aircraft is the first flight of the day, when
runway surface conditions have changed since last landing and/or
when there is no air traffic controller process to check/relay this
information to the aircraft. Also in some cases, there may be
limited levels of braking which the pilot may have to manually
input into the braking system via selector switch based on air
traffic controller's estimate of the runway conditions. This may
lead to a safe/conservative usage of braking which may be
significantly below the optimum achievable braking and extend the
braking distance. Hence time to exit the runway increases,
constraining airport runway capacity.
SUMMARY
[0005] System and method for aircraft braking based on real time
runway condition are disclosed. In one aspect, during landing, real
time data of runway condition may be obtained using at least one
sensor disposed around an aircraft. At least one brake factor may
be determined based on the real time data of the runway condition.
Aircraft braking may be dynamically controlled based on the at
least one brake factor.
[0006] According to another aspect of the present subject matter, a
system includes at least one sensor disposed around an aircraft,
and a computational unit communicatively connected to the at least
one sensor. In operation, the computational unit determines at
least one brake factor based on the real time data of the runway
condition. The system further includes a brake control unit to
control aircraft braking based on the at least one brake
factor.
[0007] According to another aspect of the present subject matter, a
non-transitory computer-readable storage medium including
instructions that are executed by a computational unit to perform
the method described above.
[0008] The system and method disclosed herein may be implemented in
any means for achieving various aspects. Other features will be
apparent from the accompanying drawings and from the detailed
description that follow.
BRIEF DESCRIPTION OF THE DRAWINGS
[0009] Various embodiments are described herein with reference to
the drawings, wherein:
[0010] FIG. 1 illustrates a block diagram of an example onboard
aircraft brake control system;
[0011] FIGS. 2A-2D illustrate example schematic diagrams for
progressively determining brake factors for runway sub-regions
based on real time runway condition;
[0012] FIG. 3 illustrates a top view of an example schematic
diagram showing the runway sub-regions;
[0013] FIG. 4 illustrates an example flow diagram for aircraft
braking based on real time runway condition;
[0014] FIG. 5 illustrates an example flow diagram for aircraft
braking based on real time hyperspectral image data of runway;
and
[0015] FIG. 6 illustrates an example block diagram of a computing
system for aircraft braking based on real time runway
condition.
[0016] The drawings described herein are for illustration purposes
only and are not intended to limit the scope of the present
disclosure in any way.
DETAILED DESCRIPTION
[0017] In the following detailed description of the embodiments of
the present subject matter, references are made to the accompanying
drawings that form a part hereof, and in which are shown by way of
illustration specific embodiments in which the present subject
matter may be practiced. These embodiments are described in
sufficient detail to enable those skilled in the art to practice
the present subject matter, and it is to be understood that other
embodiments may be utilized and that changes may be made without
departing from the scope of the present subject matter. The
following detailed description is, therefore, not to be taken in a
limiting sense, and the scope of the present subject matter is
defined by the appended claims.
[0018] Embodiments described herein provide an aircraft braking
based on real time runway condition. Example runway condition may
be dry, wet, and/or contaminated. The term "dry runway" may refer
to the runway which is clear of contaminants and visible moisture.
The term "wet runway" may refer to the runway which is neither dry
nor contaminated is considered wet. The term "contaminated runway"
may refer to the runway which is covered by elements such as ice,
slush, brine, gravel, debris (e.g., rubber debris of aircraft
tyres), salt, oil, fuel, rain water, dry/wet/compact snow, and/or a
combination thereof. The runway condition may depend on a runway
surface type, elements/composition of the contaminants on top of
the runway, contaminants type, extent of coverage/area of the
contaminants, and a thickness/depth of the contaminants present on
the runway. Example runway surface type may be asphalt and/or
concrete.
[0019] Depending on the runway condition, a safe reduction value
may be applied to a brake factor. The terms "brake factor" and
"friction factor" may be used interchangeably throughout the
document. The brake factor may refer to an aircraft braking
coefficient (.mu.) that is used to perform braking operations. The
aircraft braking coefficient is dependent on a surface friction
between aircraft wheels and the runway corresponding to the runway
condition. Less friction means less aircraft braking coefficient
and less aircraft braking response. For example, in case of the dry
runway, the surface friction may be high and therefore a
normal/high aircraft braking coefficient (e.g., .mu. of value
0.35-0.4 or above) may be applied for aircraft braking. For the
wet/contaminated runway, the surface friction (i.e., grippability
between aircraft wheels and the runway) may be low and therefore a
reduction value may be applied to the normal aircraft braking
coefficient (e.g., .mu. of value 0.25-0.3 or below). For example,
the reduction value may be determined based on the runway
condition.
[0020] Examples described herein provide an enhanced system,
technique and a method for aircraft braking based on real time
runway condition. In one example, real time data of runway
condition may be obtained, during landing, using at least one
sensor disposed around an aircraft. Further, at least one brake
factor may be determined based on the real time data of the runway
condition. Furthermore, aircraft braking may be dynamically
controlled based on the at least one brake factor.
[0021] FIG. 1 illustrates a block diagram 100 of an example
onboard-aircraft braking control system 102. The aircraft braking
control system 102 can be disposed in an aircraft for controlling
the aircraft braking. The aircraft braking control system 102
includes at least one sensor 104, a database 106, a computational
unit 108, and a brake control unit 112. The sensor 104 may be
disposed around the aircraft. Example sensor 104 may be an imaging
device such as a hyperspectral camera and/or a multispectral
camera. The camera may include a field-of-view within which the
runway can be monitored. The computational unit 108 and the brake
control unit 112 can be any combination of hardware and programming
to implement the functionalities described herein. Example the
computational unit 108 and the brake control unit 112 can include a
processor.
[0022] Further, the computational unit 108 may be communicatively
connected to the sensor 104 and the database 106. The database 106
may store look-up table 110 associated with correlation data of
spectrum of contaminants, pre-stored runway conditions 1108 (e.g.,
contaminant types and depth of contaminants) associated with the
runway and a set of pre-stored braking factors 110C corresponding
to the pre-stored runway conditions. Each of the set of pre-stored
brake factors 110C may correspond to different runway conditions.
Example correlation data of spectrum of contaminants may include a
set of reference spectral bands and intensities 110A corresponding
to a known contaminant set. Example pre-stored runway conditions
1108 may include a runway surface type, elements/composition of the
contaminants on top of the runway, contaminants type, an extent of
coverage/area of the contaminants, segment-wise distribution of
contaminants on the runway, and depth of the contaminants present
on the runway.
[0023] In operation, the sensor 104 may determine real time data of
the runway condition during landing. In one example, an imaging
device (i.e., sensor 104) may generate hyperspectral image data
(i.e., real time data) including sensed spectral bands and
intensities that correspond to the runway image within the
field-of-view of the sensor 104. The imaging device may include
built in visual/infrared/spectrometric filters for spectral
scanning. Thereby, the hyperspectral image may include feature data
such as spatial and hyperspectral information (e.g., spectral bands
and associated intensities) in each pixel. This spatial and
hyperspectral information may be used to identify the contaminants
present on the runway surface, the area/surface of
coverage/contamination, segment-wise distribution of contaminants
on the runway, depth of contaminants on the runway, and the
background (e.g., runway surface such as concrete/asphalt).
[0024] Further in operation, the computational unit 108 may obtain
the real time data of runway condition from the sensor 104.
Further, the computational unit 108 may determine at least one
brake factor based on the real time data of the runway condition.
In one example, the runway may be partitioned into multiple runway
sub-regions. The terms "runway sub-region" and "runway segment" may
be used interchangeably throughout the document. The runway
sub-regions may be of any size, shape, length, width, and/or
dimension without deviating from the scope of the present subject
matter. Further, the runway condition associated with each runway
sub-region within a field-of-view of the sensor 104 may be
determined by analyzing the obtained real time data. The runway
condition associated with each runway sub-region may progressively
determined while the aircraft approaches each runway sub-region.
This is explained in detail with respect to FIGS. 2A-2D.
[0025] In one example, the computational unit 108 determines the
runway condition by extracting the feature data, such as spectral
and spatial information, from the obtained real time hyperspectral
image data. The computational unit 108 detects the presence of
contaminants on each runway sub-region using the extracted feature
data. In one example, the computational unit 108 may determine the
contaminants on each runway sub-region by comparing the extracted
feature data with the set of reference spectral bands and
intensities corresponding to the known contaminant set. Further,
the computational unit 108 may determine the depth of the
contaminants contaminating the background (i.e., runway surface).
Furthermore, the computational unit 108 generates a map of each
runway sub-region with contaminant patches in the direction of
motion of the aircraft based on the determined contaminants and the
depth of the contaminants on the runway. In addition, the
computational unit 108 may determine the contaminated patches
(i.e., runway condition) corresponding to each runway sub-region
which is likely to be encountered in line of undercarriage/wheels
of the aircraft using the generated map.
[0026] For example, the runway sub-region/segment condition is
determined as "contaminated patches" with standing water patch of 6
mm depth extending as layer-1, compact ice of 3 mm depth as layer-2
below the layer-1, slush and rubber debris extending for 20 feet on
a concrete runway surface.
[0027] Furthermore in operation, the computational unit 108 may
determine the brake factors associated with each runway sub-region
based on the corresponding runway conditions (i.e., contaminated
patches in line of the undercarriage/wheels of the aircraft). In
one example, the computational unit 108 may compare/correlate the
determined contaminated patches in line of the undercarriage/wheels
of the aircraft with pre-stored runway conditions in the look-up
table 110. The computational unit 108 may determine brake factors
corresponding to each runway sub-region from the set of pre-stored
brake factors based on the real time comparison/correlation. In one
example, a brake factor corresponding to a runway sub-region is
determined when the determined runway condition associated with the
runway sub-region substantially matches with the pre-stored runway
condition in the look-up table 110. The set of pre-stored brake
factors may correspond to different runway conditions and augmented
based on database updation associated with the runway
condition.
[0028] FIGS. 2A-2D illustrate example schematic diagrams for
progressively determining brake factors for runway sub-regions
based on real time runway condition. FIGS. 2A-2D show an aircraft
202 and a sensor 204 disposed at nose of the aircraft 202. In other
example, the sensor 204 may also be disposed in front of cockpit,
tail tip of the aircraft 202 and/or the like. Further, FIGS. 2A-2D
show a runway 206 partitioned into multiple runway sub-regions
206A-N. In other words, each runway sub-region can be progressively
identified within field-of-view ".theta." of the sensor 204 while
the aircraft 202 approaches toward the runway 206 for landing.
[0029] As shown in FIG. 2B, the real time hyperspectral image of
the runway sub-region 206A within the field-of-view ".theta." of
the sensor 204 may be generated when the aircraft 202 approaches
toward (i.e., before approaching the runway) the runway 206. The
contaminated patches (i.e., runway condition) associated with the
runway sub-region 206A may be determined by analyzing the real time
hyperspectral image of the runway sub-region 206A. Further, a brake
factor .mu..sub.1 associated with the runway sub-region 206A may be
determined based on the contaminated patches present on the top of
the runway sub-region 206A using the process explained in FIG. 1.
Furthermore, the brake factor .mu..sub.1 and associated runway
condition may be updated to the database 106 or fed to the brake
control unit 112 (as shown in FIG. 1).
[0030] As shown in FIG. 2C, when the aircraft 202 enters the runway
sub-region 206A, the brake factor .mu..sub.1 may be fed to the
brake control unit 112, for example, via a transmission medium
(e.g., wired or wireless transmission). At the same time, the
sensor 204 may cover the runway sub-region 206B, accordingly
contaminated patches (i.e., runway condition) associated with the
runway sub-region 206B may be determined. Further, the brake factor
.mu..sub.2 associated with the runway sub-region 206B may be
determined based on the contaminated patches present on the top of
the runway sub-region 206B. As aforementioned, the brake factor
.mu..sub.2 and associated runway condition may be dynamically
updated to the database 106.
[0031] As shown in FIG. 2A, consider automatic/manual brake
activation is made in the runway sub-region 206A, so that the
aircraft brake may be applied when the aircraft 202 rolls-down at
runway sub-region 206B. In example shown in FIG. 2D, when the
aircraft 202 crosses from the runway sub-region 206A and enters the
runway sub-region 206B, the brake factor .sub.112 corresponding to
the runway sub-region 206B may be fed to the brake control unit
112. Thereby, the aircraft braking for the aircraft 202 traversing
in the runway sub-region 206B may be dynamically controlled based
on the brake factor .mu..sub.2. Similarly, the braking factor for
each runway sub-region is dynamically determined and inputted to
the braking control unit 112 till the aircraft 202 comes to halt or
the landing operation is completed.
[0032] The brake control unit 112 may be communicatively coupled to
the database 106 and the computational unit 108. In operation, the
brake control unit 112 may control aircraft braking based on the
brake factors corresponding to each runway sub-region. In one
example, the brake control unit 112 may control aircraft braking
using the brake factors associated with each runway sub-region when
the aircraft encounters a corresponding runway sub-region upon
touch-down of the aircraft.
[0033] In one example, during landing phase, the braking parameters
associated with the brake factors may be provided as input
automatically to the braking unit (not shown in FIG. 1). Yet in
another example, the braking parameters may be provided as input to
the braking unit upon validation from the pilot.
[0034] Further, the determined brake factors may be relayed through
a transmission medium to the aircraft brake control unit 112 or an
on-board aircraft system (e.g., braking distance
computer/brake-to-vacate (BTV), runway-overrun protection system
(ROPS), on-board airport navigation system (OANS), and
airborne/ground-air/satellite-air). For example, the on-board
aircraft system may calculate a braking performance of the aircraft
202 with respect to the landing runway 206 and automatically
factors in differences in performance over different runway
sub-regions 206A-N to extract maximum braking efficiency that
corresponds to a real-time runway condition. In another example,
the OANS system may automatically suggest the optimal exit point
with the allowable optimum speed based on the relayed data.
Thereby, the taxiing distance, time-to-vacate, and fuel consumption
of the landing aircraft may be minimized.
[0035] Autonomously, the system 100 may provide the real-time
runway condition assessment for the aircraft-on-approach without
involving manual entry, selection procedures, and chart
updates.
[0036] FIG. 4 illustrates the flow diagram 400 for aircraft braking
based on real time data of runway condition. At block 402, real
time data of runway condition may be obtained using at least one
sensor disposed around an aircraft, during landing. In one example,
the real time data may be hyperspectral image data. The
hyperspectral image data may include spectral bands and intensities
that correspond to the full image (i.e., runway image) in the
field-of-view of the sensor.
[0037] At block 404, at least one brake factor may be determined
based on the real time data of the runway condition. The brake
factor may include an aircraft braking coefficient that depends on
a surface friction (i.e., grippability) between aircraft wheels and
the runway. In one example, the runway may be partitioned into
multiple runway sub-regions. Further, the runway condition (i.e.,
contaminated patches in line of the undercarriage/wheels of the
aircraft) associated with each runway sub-region within a
field-of-view of the sensor may be determined by analyzing the
obtained hyperspectral image data. The brake factors associated
with each runway sub-region may be determined based on the
determined runway condition. Furthermore, the runway condition
associated with each runway sub-region may be progressively
determined while the aircraft approaches each runway
sub-region.
[0038] At block 406, aircraft braking may be controlled based on
the at least one brake factor. In one example, the aircraft braking
may be controlled by using the brake factors associated with each
runway sub-region when the aircraft encounters a corresponding
runway sub-region upon touch-down of the aircraft. This is
explained in more detail in FIG. 5.
[0039] FIG. 5 illustrates the flow diagram 500 for aircraft braking
based on real time hyperspectral image data of runway. At block
502, real time hyperspectral image data of multiple runway
sub-regions may be obtained using at least one sensor disposed
around an aircraft, during landing. At block 504, feature data
including spectral and spatial information may be extracted from
the obtained real time hyperspectral image data. At block 506,
contaminants on each runway sub-region may be determined by
comparing extracted feature data with a set of reference spectral
bands and intensities corresponding to a known contaminant set.
[0040] At block 508, depth of the contaminants on each runway
sub-region may be determined. At block 510, a map of each runway
sub-region with contaminant patches in the direction of motion of
the aircraft may be generated based on the contaminants and the
depth of the contaminants. At block 512, the contaminated patches
corresponding to each runway sub-region which is encountered in
line of undercarriage/wheels of the aircraft may be determined
using the generated map.
[0041] At block 514, brake factors associated with each runway
sub-region that is in line of undercarriage/wheels of the aircraft
may be determined by correlating the determined contaminated
patches in line of undercarriage/wheels of the aircraft with
pre-stored runway conditions. In one example, brake factors
corresponding to each runway sub-region may be determined from a
set of pre-stored brake factors when the determined contaminated
patches matches with a pre-stored runway condition. The set of
pre-stored brake factors correspond to different runway conditions.
At block 516, aircraft braking in line of undercarriage/wheels of
the aircraft may be dynamically controlled based on the determined
brake factors.
[0042] FIG. 6 illustrates a block diagram of an example computing
system 600 for controlling aircraft braking based on real time
runway condition. The computing system 600 includes a processor 602
and a machine-readable storage medium 604 communicatively coupled
through a system bus. The processor 602 may be any type of central
processing unit (CPU), microprocessor, or processing logic that
interprets and executes machine-readable instructions stored in the
machine-readable storage medium 604. The machine-readable storage
medium 604 may be a random access memory (RAM) or another type of
dynamic storage device that may store information and
machine-readable instructions that may be executed by the processor
602. For example, the machine-readable storage medium 604 may be
synchronous DRAM (SDRAM), double data rate (DDR), Rambus.RTM. DRAM
(RDRAM), Rambus.RTM. RAM, etc., or storage memory media such as a
floppy disk, a hard disk, a CD-ROM, a DVD, a pen drive, and the
like. In an example, the machine-readable storage medium 604 may be
a non-transitory machine-readable medium. In an example, the
machine-readable storage medium 604 may be remote but accessible to
the computing system 600.
[0043] The machine-readable storage medium 604 may store
instructions 606-610. In an example, instructions 606-610 may be
executed by the processor 602 for performing aircraft braking based
on real time data of runway condition.
[0044] Some or all of the system components and/or data structures
may also be stored as contents (e.g., as executable or other
machine-readable software instructions or structured data) on a
non-transitory computer-readable medium (e.g., as a hard disk; a
computer memory; a computer network or cellular wireless network or
other data transmission medium; or a portable media article to be
read by an appropriate drive or via an appropriate connection, such
as a DVD or flash memory device) so as to enable or configure the
computer-readable medium and/or one or more host computing systems
or devices to execute or otherwise use or provide the contents to
perform at least some of the described techniques. Some or all of
the components and/or data structures may be stored on tangible,
non-transitory storage mediums. Some or all of the system
components and data structures may also be provided as data signals
(e.g., by being encoded as part of a carrier wave or included as
part of an analog or digital propagated signal) on a variety of
computer-readable transmission mediums, which are then transmitted,
including across wireless-based and wired/cable-based mediums, and
may take a variety of forms (e.g., as part of a single or
multiplexed analog signal, or as multiple discrete digital packets
or frames). Such computer program products may also take other
forms in other embodiments. Accordingly, embodiments of this
disclosure may be practiced with other computer system
configurations.
[0045] It may be noted that the above-described examples of the
present solution is for the purpose of illustration only. Although
the solution has been described in conjunction with a specific
embodiment thereof, numerous modifications may be possible without
materially departing from the teachings and advantages of the
subject matter described herein. Other substitutions, modifications
and changes may be made without departing from the spirit of the
present solution. All of the features disclosed in this
specification (including any accompanying claims, abstract and
drawings), and/or all of the steps of any method or process so
disclosed, may be combined in any combination, except combinations
where at least some of such features and/or steps are mutually
exclusive.
[0046] The terms "include," "have," and variations thereof, as used
herein, have the same meaning as the term "comprise" or appropriate
variation thereof. Furthermore, the term "based on", as used
herein, means "based at least in part on."
[0047] The present description has been shown and described with
reference to the foregoing examples. It is understood, however,
that other forms, details, and examples can be made without
departing from the spirit and scope of the present subject matter
that is defined in the following claims.
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