PROCESS : SEPARATION ASSURANCE 30/05/2014 Context Introduction - PowerPoint PPT Presentation

HYBRID MODELING AND AUTOMATION OF AIR TRAFFIC CONTROLLER DECISION PROCESS : SEPARATION ASSURANCE 30/05/2014

Context Introduction  Dynamic Modeling of the ATC Process  Aircraft Dynamic  Model for Flight Management System  Flight Plan  Decision Process of ATCO  Decision Mechanism of Enroute Controller  Decision Mechanism of Approach Controller  Hybrid System Modeling of Air Traffic Controller  ACC Finite State Automaton  APP Finite State Automaton  Algorithm for Automated Safety Assurance  ACC Algorithm  APP Algorithm  Implementation and Results  Conclusions  Future Works 

I. Introduction

Air Traffic Growth  The system is still reliable but air transport goes on to grow. [Source: ICAO, Airbus]

Air Traffic Growth From The View of ATCO 2030 2014 How do you handle this?

Human Decision Making  Human decision making:  complex  Innovative but only for smaller problem size!

Automation tools for APP and ACC  Goal : Automation tools which perform routine separation provision tasks of controller for two different types of flight modes.  Arrival/Departure (APP)  En-route (ACC) operations  We utilize hybrid automata formalism for both of these flight modes.

Air Traffic Management Structure [Taken from Overview of ATC Systems and Processes , Prof. Hamsa Balakrishnan]

Our Focus Detailed model for one aircraft (> 5 min) The main subject of this study: ACC APP

II. Dynamic Model of the ATC Process

II. Dynamic Model of the ATC Process  We use an aircraft and flight management model to simulate of Air Traffic Control (ATC) actions.  based on Lygeros and Glover’s model [Lygeros,2007]  We revise the model in some aspects as seen in figure:

A. Aircraft Dynamic  Point Mass Model (PMM)  The state variables of the aircraft are:         the horizontal position (x 1 and x 2 ) x cos x cos u w 4 5 3 1         altitude (x 3 ) x sin x cos u w   4 5 3 2       the true airspeed (x 4 ) x sin u w   4 3 3      2  the heading angle (x 5 ) C S x x u       D 3 4 1 x g sin u   3 2 x x  the mass of the aircraft (x 6 )   6 6      C S x x    The control inputs of the aircraft are: L 3 4  sin u  2 2 x   6  the engine thrust (u 1 )       u 1  the bank angle (u 2 )  the flight path angle (u 3 )

B. Model for Flight Management System  The FMS works like a controller. u = f(x, flight plan, ATC actions)  FMS model has 8 discrete modes. These discrete modes are:  flight level (FL)  way-point index (WP)  acceleration mode (AM)  climb mode (CM)  speed hold mode (SHM)  flight phase (FP)  reduced power mode (RPM)  troposphere mode (TrM)

Finite State Machines for Flight Manegement System These modes are defined relative to BADA for determination of control inputs. Detailed information about these modes can be reached at [Lygeros, 2007] Finite state machine for AM Finite state machine for FL

FMS Controller  FMS controller can be divided into two components:  First one is vertical and along track motion control with u1 (thrust) and u3 ( flight path angle)  The second one is horizontal motion control with u2 (bank angle)

C. Flight Plan  We use a flight plan data set which includes sequence of way- points, in three dimensions.  Way-point data come from point profile of ALLFT+ data set [PRISME Data]  ALLFT+ :

point profile of ALLFT+ data set:

Progression to FMS Model  Flight plan is captured from ALLFT+ data  The speed profile is evaluated from BADA model [Sample for BADA performance file]

III. Decision Process of ATCO

III. Decision Process of ATCO  We determine the decision process of ATCOs speaking with real air traffic controllers and convert these processes to hybrid models. nlatim Decision Process of Air Traffic Controller [Garcia-Avello, 1997]

Decision Process of ATCO  Decision process of Air Traffic Controller:  evaluates information  analyses current situation  monitors flights  estimates routes  detects the problem  finds solution Decision Process of Air Traffic Controller [Garcia-Avello, 1997]

A. Decision Mechanism of En Route Controller  checks flight levels  Controller checks flight routes. If:  Controller checks horizontal separation (5 nm) at intersection point and longitudinal separation (10 nm ) after intersection point. If any separation losses:  command direct routing, or  altitude change, or  delaying motions  If:  Controller checks horizontal separation (5 nm). If any separation losses:  command direct routing, or  heading angle change

B. Decision Mechanism of Approach Controller  Controller sequences arrival flights relative to the estimated arrival time. If any separation losses are estimated between arrival flights:  delaying motions  If any separation losses are estimated between departure flights:  command direct routing, or  delaying motions

B. Decision Mechanism of Approach Controller  If any separation losses are estimated between departure flight and arrival flight:  command direct routing, or  delaying motion, or  horizontal motion at a defined altitude Horizontal motion

IV. Hybrid System Modeling of Air Traffic Controller

A. ACC Finite State Automaton  ACC Finite State Automaton has eight discrete states which symbolize defined controller actions:  q 0 is initial state which refer to no action.  q 1 denotes direct routing for first aircraft  q 2 denotes altitude change for first flight  q 3 denote delaying motion for second flight with reducing of speed  q 4 denote delaying motion for second flight with vector for spacing  q 5 denotes altitude change for second flight  q 6 denotes direct routing for both of them  q 7 denotes bank angle for both of them

A. ACC Finite State Automaton  The logic definitions for transition functions and helper functions are:         and , or a , a is 1, a not a a is 0                   e a a a a a a a a a a a a 1 0 0 1 0 1 2 4 0 1 2 4 3                e a a a a a a a a a   2 0 1 2 4 3 0 1 2 4         e a a a a a a 3 0 1 2 4 3 5       e a a a a 4 0 1 4 5       e a a a a 5 0 1 4 2        e a a a a a 6 0 1 4 2 5     e a a 7 0 5       e a a a a 8 0 1 4 5

B. APP Finite State Automaton  APP Finite State Automaton has seven discrete states:  q 0 is initial state which is defined as no action  q 1 denotes direct routing for second flight (departure flight)  q 2 denotes delaying motion for second flight which is applied with reducing of speed (ROCD)  q 3 denotes horizontal motion for second flight at a defined altitude. In q 3 , departure flight are climbed to a defined altitude, moved along track and climbed to original route for separation with arrival flight q3

B. APP Finite State Automaton  q 4 denotes delaying motion for first flight  q 5 denote delaying motion for second flight with vector for spacing  q 6 denote delaying motion for second flight with reducing of speed

B. APP Finite State Automaton  The relation between transition functions and helper functions are:         and , or a , a is 1, a not a a is 0    e a a a 1 0 2 3             e a a a a a a 2 0 2 0 2 3 6    e a a a 3 1 2 3               e a a a a a a a a 4 1 2 5 1 2 3 5 6  e a 5 4    e a a a 6 4 5 7           e a a a a a a 7 0 2 0 2 3 6           e a a a a a a 8 1 2 1 2 3 6   e a a 9 4 7

V. Algorithm for Automated Safety Assurance

A. ACC Algorithm  The algorithm generalizes ACC Automaton to multi-flight handling within the sector. Algorithm 1: ACC Controller Algorithm input : Flight plans of all enroute flights and current state variables output : Controller actions and new flight routes of all enroute flights 1 if then a new aircraft comes to sector 2 Check separation of all flights in sector 3 if then any unseparated flight exist 4 for to | do all unseparated flights in sector 5 Set flight1 to most old aircraft in unsepareted flights 6 for to | do all unseparated flights with flight1 7 Set flight2 to most close unseparated flight to flight1 8 Generate controller action from ACC Automata for flight1 and flight2 9 Set new flight1 and new flight2routes to new flight routes