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

0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

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

0.6

0.5

0.4

0.3

0.2

0.1

0 60 80 100 120 s f =5m =0º 140 160 180 0.4

0.3

0.2

0.1

0 60 1 0.9

0.8

0.7

0.6

0.5

80 100 120 s =10m f =0º 140 160 180 1 0.9

0.8

0.7

0.6

0.5

0.4

0.3

0.2

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

0.7

0.6

0.5

0.4

0.3

s f =10m =45º 80 100 120 140 160 180 real distance (m) 1 0.9

0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

0 60 s =15m f =0º 80 100 120 140 160 180 1 0.9

0.8

0.7

0.6

0.5

0.4

0.3

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