Rami El Mawas CE 291

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Transcription:

Rami El Mawas <rami@berkeley.edu> CE 29

Outline Introduction Conclusion Modeling Building ASDI Raw Data

Introduction Introduction, Motivation, problem Statement, ATC Workload Factors, Fixed vs Dynamic boundaries, Big Picture

Introduction Air traffic controllers are persons who operate the air traffic control system to expedite and maintain a safe and orderly flow of air traffic. They typically accepts traffic from, and ultimately passes traffic to, the control of a Terminal Control Center or of another Center. Sector are geographic subdivisions in the airspace. Every sector belongs to a center.

Motivation Humans in charge: Air Traffic Controllers How to improve their job? Objective : minimize the workload of the Air Traffic Controllers Problem : the complexity of NAS Approach chosen in this project : dynamic boundaries

Problem Statement The main purpose is here to move the boundaries of the sectors in order to decrease the air traffic controller workload. By focusing only on en-route sectors, the choice of the Air Traffic Controller workload metric which was made is the peak count in a sector. How to resectorize the national air space (NAS) so that the maximum peak count of aircrafts per polygon is as small as possible. Analyzing flight plan is implicated directly into capacity distribution of the system

ATC Workload Factors The primary difficulty in modeling the ATC workload is to select the most relevant factors amongst the many potential variables affecting it: the number of aircraft (which contains peak counts), the presence of conflicts (number of intersections), the climbing and descending flights (traffic mix with arrivals, departures and overflights), the sector itself (geometry, size), the coordination and of course the traffic flow structure

Fixed vs Dynamic Boundaries Fixed boundaries: start with an initial sectorization setting and then change the center to which sectors belong. Dynamic boundaries: change the geometry of the sectors

Modeling Flow Model, Grid Model, Hybrid Model

Big Picture Flow Model ASDI Occupancy Grid Weighted graph Spectral Bisection Geometric Sector Construction

Flow Model This model is able to give a graph representing the main flows for the NAS by aggregating the routes at a sector level.

Large Capacity Cell Transmission Model. Charles Robelin & Dengfeng Sun Flow Model

Flow Model

Occupancy Grid 2 3 2 Compute cumulative or peak number of aircrafts for every cell. Model developed by S. Martinez 0 0

Occupancy Grid

Occupancy Grid

Hybrid Model 7 5 4 4 6 5 3 4 3 4 Use any Clustering Algorithm to influence all the cells by a node. Region growing or K- mean 2 2

Hybrid Model 5 6 7 2 3 4 2 3 4 5 4 4 3 3 3 6 0 2 2 3 0 Add the count in each cell affected by the corresponding nodes. Now we have weighted nodes

Spectral Bisection It is based on the Laplacian Matrix - Keep highestconnectivity - Cut the least edges. Repeat the same but with constraints are: number of sectors (actual number) or max peak count (less than limit)

Sector construction 7 6 53 46 Use Influence area 3 3 2

Occupancy Grid

Sector construction 7 6 5 4 Use Voronoi diagrams 3 2

Occupancy Grid

Building ASDI Raw Data ASDI format, script language, PScript, Route finder, ICAO/IATA

Big Picture Airline Tables IATA O/D ICAO O/D Routes ASDI

Big Picture AF BA MEA ASDI

ASDI Data ASDI is an acronym for Aircraft Situation Display to Industry. The ASDI data stream is a service made available through the U.S. Department of Transportation's Volpe Transportation Center. The ASDI stream consists of data elements which show the position and flight plans of all aircraft in U.S. and optionally, UK airspace

ASDI Data (text file) 0AF09235440KSDFTZ N604GW/673 242 088 3908N/08609W 0A2009235446KSDFTZ FFT608/427 343 0 3949N/0864W 0A209235452KSDFTZ N327N/68 096 045 3850N/08542W 0A220923544KDENTZ FFT494/587 323 30 400N/0409W 0A230923544KDENTZ SKW6284/952 204 072 3957N/0442W 0A2409235447KDENTZ QXE480/5 273 55 396N/0408W 0A2509235447KDENTZ EJA394/08 83 070 3936N/045W 0A2609235453KDENTZ NWA546/029 322 20 4004N/0428W 0AF09235440KSDFTZ N604GW/673 242 088 3908N/08609W 09 : day 23 : hour 54 : min 40 : sec 3908N : latitude 39 degre 08 min 08609W : longitude 086 degre 09 min 088 : FL

ASDI Data (xml file) <asdimessage sourcefacility="kzkc" sourcetimestamp="2007-0-3t8:59:50.0z"> <trackinformation> <nxcm:aircraftid>n54ns</nxcm:aircraftid> <nxcm:computerid> <nxce:idnumber>254</nxce:idnumber> </nxcm:computerid> <nxcm:speed>493</nxcm:speed> <nxcm:reportedaltitude> <nxce:assignedaltitude> <nxce:simplealtitude>244c</nxce:simplealtitude> </nxce:assignedaltitude> </nxcm:reportedaltitude> <nxcm:position> <nxce:latitude> <nxce:latitudedms degrees="38" minutes="9" direction="north </nxce:latitude> <nxce:longitude> <nxce:longitudedms degrees="088" minutes="52" direction="we </nxce:longitude> </nxcm:position> </trackinformation> </asdimessage>

Script Language Scripting languages (commonly called scripting programming languages or script languages) are computer programming languages that are typically interpreted and can be typed directly from a keyboard. Thus, scripts are often distinguished from programs, because programs are converted permanently into binary executable files (i.e., zeros and ones) before they are run. Scripts remain in their original form and are interpreted command-by-command each time they are run.scripts were created to shorten the traditional edit-compile-link-run process.

Script Language: PScript Data retrieval s(n:n2), s(n), s(n:), s( val ) i(n:n2), i(n), i(n:), i( val ) ls(in,in2,in3, ) where in:=s,i,or *, *(n) Logical or(in,in2, ) where in:=s,i,ls if(in) where in:=s,i,ls,or,not not(in) where in:=s,i,ls,or

Script Language: PScript Loops hloop(n), hloop(n:) vloop(n), vloop(n:) Other end break jump(n)

Route Finder Using the Aeronautical Information Management tools developed by the company ASA srl (Italy founded in 99), RouteFinder offers a powerful set of tools aimed at effective flight planning (on PC flight simulation envinronment only!) They have set up a custom PHP interface script that we can query via HTTP

Route Finder

Route Finder ID DIST Coords Name/Remarks -------------------------------------------------------------------------------------------------- LFPG 0 N49 00'46.00" E002 33'00.00" CHARLES DE GAULLE NURMO 49 N49 49'34.00" E002 45'9.00" NURMO DIPER 4 N50 20'45.00" E002 03'4.00" DIPER VESAN 2 N50 22'9.00" E002 0'35.00" VESAN RATUK 23 N50 39'25.00" E00 38'.00" RATUK SOVAT 0 N50 46'46.00" E00 28'00.00" SOVAT SANDY 23 N5 03'5.00" E00 04'03.00" SANDY EGLL 63 N5 28'39.00" W000 27'4.00" HEATHROW Charles De Gaulle to Heathrow Airport

ICAO vs IATA Codes The ICAO airport code or location indicator is a fourletter alphanumeric code designating each airport around the world. These codes are defined by the International Civil Aviation Organization.The ICAO codes are used by air traffic control and airline operations such as flight planning. An IATA airport code, also known an IATA location identifier, IATA station code or simply a location identifier, is a three-letter code designating many airports around the world, defined by the International Air Transport Association (IATA). The characters prominently displayed on baggage tags attached at airport check-in desks are an example of a way these codes are used.

Big Picture Airline Tables IATA O/D ICAO O/D Routes ASDI

Airline Companies Timetable All airline company issue every 7 months a detailed timetable of all its air flights: Origin, Desitination, Local time, operating days, Depature time, arrival time, duration, validity period

Air France

PScript (example) S(3)s(' ')or(s('+'),s('-'))i(:)s(':')i(2) vloop(:) hloop(7) or(i(),s('-'))s(' ') end i(2)s('.')i(2)s(' ') cif(ls(or(i(),s()),s(' '))) or(i(),s())s(' ') end i(2)s('.')i(2)s(' ') hloop(2) cif(ls(or(i(),s()),s(' '))) or(i(),s())s(' ') end end i(2)s(':')i(2)s(' ') hloop(:) s(2)i(:) cif(s('(')) s('(')or(s(3),s(2),ls(s(),i()))s(')') end cif(s('/')) s('/') end end s(' ')or(*(),s(3),i())s(' ') i(2)s('/')i(2)s('-')i(2)s('/')i(2) end Chunk of the code that parse the AF file

Conclusion

Conclusion & Future Work Validate the Dynamic sectorization algorithm over Europe and compare the results with the actual sectors.