Transcript DATA PROCESSING TECHNIQUES FOR CONFLICT DETECTION …
DATA PROCESSING TECHNIQUES FOR CONFLICT DETECTION ON AIRPORT SURFACE
J. García Herrero 1 , J.A. Besada Portas 2 , Gonzalo de Miguel 2 , Javier Portillo 2
(1) Universidad Carlos III de Madrid. (SPAIN) (2) Universidad Politécnica de Madrid. (SPAIN)
INTRODUCTION
• Airport traffic automation
Radar SMR Databases de Radar ASR GNSS +ADS Multilateration Mode-S
INTRODUCTION
• A-SMGCS
CONTROLLER WORKING POSITION CONTROL DISPLAY PLANNING GUIDANCE SURVEILLANCE & DATA FUSION SENSORS INFORMATION SYSTEMS
AIRPORT SURFACE TERMINAL AREA Scenario: aircraft, vehicles, routes, demanded operations, runways, taxiways, stands, TMA, etc.
A SMGCS’ CONTROL FUNCTION
• • •
FUNCTION:
Analyse the traffic situation and check safety level –
Acess/Separation Rules: safety margins between aircraft and vehicles, depending on areas, visibility, conditions, …
–
Restricted Areas: areas temporarily closed or restricted to some types of mobiles
OBJECTIVE:
enough Automatically detect all the conflictive situations, with anticipation time
INFORMATION SOURCES:
Tracking from Surveillance Function and Airport DataBases
TYPES OF CONFLICTS (I)
•
RUNWAY INTRUSION CONFLICTS
(1.2) (1.1)
RWY 1
(1.3)
RWY 2
TYPES OF CONFLICTS (II)
•
SEPARATION CONFLICTS
(5.1.1) TAXIWAY COLLISION TAXIWAY (5.1.2) COLLISION
TYPES OF CONFLICTS (III)
• •
NON-AUTHORISED MOVEMENTS DEVIATIONS FROM GMP
RUNWAY (2.1) (last point)
EXIT
COLLISION (2.3) TAXIWAY wrong direction COLLISION RUNWAY non-taxiing runway (2.2) TAXIWAY (1.1) (1.4)
TRACK LIST
FUNCTION STRUCTURE
EXTRA POLATION GMP PAIR SELECTION AIRPORT LAYOUT AIRCRAFT VEHICLES COLISION CONFLICTS
ALARMS
-INTRUSION -NON-AUTH.
-GMP DEV.
CONFLICTS
LOCATION ON MAP
2K t 2K l covered area in element 2 , estimated position covered area in element 1
Airport representation Location with uncertainty
DETECTION LOGIC
• INTRUSION CONFLICTS
RUNWAY ACTIVATION terminal area take-off threshold SEARCH ON LINKED AREAS runway hot area close exitways, taxiways,...
DETECTION LOGIC
• SEPARATION CONFLICTS
LOC. ON AIRPORT LAYOUT
DISTANCE 2 v 2
PAIRS SEARCH ON SAME AND LINKED AREAS
v 1 d min
minimum separation
DETECTION LOGIC
• SEPARATION CONFLICTS (II)
B D A C
A,B: head-on approaches C,D: tail-chase approaches
•
CONFLICT DETECTION CRITERION
Several components in definition of separation:
–
Minimum physical distance (SEP min ):
safe separation in any case –
Minimum Relative Separation (MRS) :
minimum separation in ideal estimation, function(relative positions, relative velocities) 800 600 400 200 0 -200 -400 -600 -1000 -500 0 500 1000 V1=25m/s V2=5,15,25,40 m/s –
Alarm Threshold:
takes into account uncertainty in positions estimated/extrapolated
SEP min MRS AT
STATISTICAL MODEL
•
Model uncertainty in tracking information:
–
observation, estimation, extrapolation,…
STATISTICAL MODEL
10 • • –
Test Design:
H 0 : H 1 : 2 x 1 2 y 1 d Th 2 x 1 2 y 1 d Th 5 0 RM CRITICAL
Three alternatives analysed:
– – REGION -5 -5 0
Bound to conflict region probability Test
2 over worst case in critical region’s edge (Haest95)
5
Linear approximation to estimated distance
distance reached with probability P D conflict region d Th z s d d measured 10
SOME RESULTS (I)
100m 125m
scenario 1
f =45º f =0º
scenario 2
0 0 1 2 3 4 6 5
Scenario 1: False Alarm probability
7 x 10 -3 0.7
s =5m 0.6
0.5
s =10m 0.4
0.3
0.2
0.1
30 35 40 0 0 5 10 5 10 15 20 time (s) 25 15 20 25 30 time (s) 35 40 0.9
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0 0 s =15m 5 10 15 20 25 time (s) 30 35 40
SOME RESULTS (II)
Scenario2: Detection probability
1 0.9
0.8
0.7
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0.2
0.1
0 60 80 100 120 s f =5m =0º 140 160 180 0.4
0.3
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0.1
0 60 1 0.9
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0.5
80 100 120 s =10m f =0º 140 160 180 1 0.9
0.8
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0.1
0 60 s f =5m =45º 80 100 120 140 160 180 real distance (m) 0.2
0.1
0 60 1 0.9
0.8
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0.3
s f =10m =45º 80 100 120 140 160 180 real distance (m) 1 0.9
0.8
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0 60 s =15m f =0º 80 100 120 140 160 180 1 0.9
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0.2
0.1
0 60 s =15m f =45º 80 100 120 140 160 180 real distance (m)
CONCLUSIONS
• Developed and analyzed data processing techniques embedded in an ASMGCS’ control system – Integration of tracking output from surveillance function (data fusion) + lateral information airport layout, airport configuration, … – Criteria for detecting the main types of surface conflicts as a function of relative situation and quality of estimations – Analysis of several statistical tests for conflict detection to attain the best levels of performance • Design: probability of detecting conflict situation (95% when d=SEPmin) – Satisfied by all alternatives • The probability of raising false alarms increases when this accuracy is lower. The best performance is attained with third alternative