2012 Simulated Car Racing Championship @ CIG-2012

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Third leg of the 2012 Simulated Car Racing Championship held during CIG-2012

More information at
http://games.ws.dei.polimi.it/competitions/scr/
http://groups.google.com/group/racingcompetition
http://www.geccocompetitions.com

Organizers
Daniele Loiacono, Politecnico di Milano
Luigi Cardamone, Politecnico di Milano
Pier Luca Lanzi, Politecnico di Milano

Published in: Technology, Sports, Automotive
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2012 Simulated Car Racing Championship @ CIG-2012

  1. 1. The 2012 Simulated Car Racing Championship @ CIG-2012 Daniele Loiacono, Luigi Cardamone, and Pier Luca Lanzi2012 Simulated Car Racing Championship @ CIG-2012
  2. 2. 2012 Simulated Car Racing Championship 9 races during 3 conferences Develop a driver for TORCS (hand-coded, learned, evolved, …) Drivers will be awarded based on their score in each conference competition At the end, the team with highest overall score wins the championship2012 Simulated Car Racing Championship @ CIG-2012
  3. 3. Roadmap of the 2012 Championship 1.  EVO*-2012, Malaga (Spain) April 11-13, 2012 2.  ACM GECCO-2012, Philadelphia (US) July 7-11, 2012 3.  IEEE CIG-2012, Granada (Spain) September 11-14, 20122012 Simulated Car Racing Championship @ CIG-2012
  4. 4. Motivations q  Proposing a relevant game-based competition " more representative of commercial games AI " more similar to a real-world problem q  Proposing a funny and exciting competition " you can see and play with the entries of this competition " human players can interact with AI " a lot of programmed AI available for comparison q  Proposing a challenging competition " computationally expensive " real-time " on-line learning " noisy sensors2012 Simulated Car Racing Championship @ CIG-2012
  5. 5. The Open RacingCar Simulator
  6. 6. The Open Racing Car Simulator & the Competition Software TORCS TORCS PATCH BOT BOT BOT SBOT SBOT SBOT q  The competition server UDP UDP UDP q  Separates the bots from TORCS q  Build a well-defined sensor model q  Works in real-time BOT BOT BOT2012 Simulated Car Racing Championship @ CIG-2012
  7. 7. Sensors and actuators q  Rangefinders for edges on the track and opponents (with noise) q  Speed, RPM, fuel, damage, angle with track, distance race, position on track, etc. q  Six effectors: steering wheel [-1,+1], gas pedal [0, +1], brake pedal [0,+1], gearbox {-1,0,1,2,3,4,5,6}, clutch [0,+1], focus direction2012 Simulated Car Racing Championship @ CIG-2012
  8. 8. What is the structure of a race? Three stages: warm up, qualifiers, actual race During warm-up, each driver can explore the track and learn something useful During qualifiers, each driver races alone against the clock (the best 8 drivers move to the race) During the race all the drivers race together2012 Simulated Car Racing Championship @ CIG-2012
  9. 9. Competitors
  10. 10. The competitors q  Four entries in 2012: " Ho Duc Thang, University of Nottingham " BFB4, Sejong Univ, Korea " Mr. Racer, TU Dortmund " Smile Sheep, Taiwan National Chiao Tung University q  Three reference entries (selected from the top entries of the past championship) : " Mariscal & Fernández, Málaga University " Ready2Win, Slovak University of Technology – FIIT " AUTOPIA, Madrid and Granada2012 Simulated Car Racing Championship @ CIG-2012
  11. 11. Ho Duc ThangUniversity of Nottingham2012 Simulated Car Racing Championship @ CIG-2012
  12. 12. Ho Duc Thang q  Hybrid fuzzy controller with a module to learn the model track as the car drives, a module to perform some simple plannings based on the modelled segments of the track and a fuzzy controller which actually drives the car. q  All the modelling, planning and driving are done during the race, the warm-up stage is not exploited q  No opponent handling2012 Simulated Car Racing Championship @ CIG-2012
  13. 13. BFB4Kyung-Joong KimJun-ho SeoTae-seong KimSejongCar Racing Championship @ CIG-20122012 Simulated Univ, Korea
  14. 14. BFB4 q  Scripted approach " Simple approach for steering and accelerating q  Jump Detection " When the Z-Sensor is more than 0.4 " While the car is jumping and landing(few times, 10 tick count), the steer of car is fixed to forward q  Opponent avoidance: " Just brake if the opponent is approached on a straight " Modify the normal steering when the opponent is approached in a bend2012 Simulated Car Racing Championship @ CIG-2012
  15. 15. Mr RacerJan Quadflieg, Tim Delbruegger and Mike PreussTU Dortmund2012 Simulated Car Racing Championship @ CIG-2012
  16. 16. Mr. Racer 2012 q  Joined effort of Jan Quadflieg, Tim Delbruegger and Mike Preuss q  Variables learned offline with the CMA-ES, now including optimized settings for recovery , the clutch and… q  NEW: Parameters of the opponent handling module have been optimized q  Optimization of the opponent handling will hopefuly result in a CIG competition paper2012 Simulated Car Racing Championship @ CIG-2012
  17. 17. Noise Handling1.  Low pass filter on sensor values2.  2 Regression polynoms are fitted to each side3.  Resample the polygons4.  Calculate our measure (see CIG paper 2010)5.  Low pass filter on the last measurements2012 Simulated Car Racing Championship @ CIG-2012
  18. 18. Online Learning during Warmup q  We learn a model of the racetrack q  One of two parameter sets is chosen q  Target speeds for all corners are then fine tuned q  All information is saved at the end of the warmup q  And later used during qualifying and the race2012 Simulated Car Racing Championship @ CIG-2012
  19. 19. Opponent Handling q  Noise filtering with a lowpass filter q  Observer module interprets filtered sensor readings q  This leads to a recommended speed and an overtaking line (created on the fly!) q  Planning module incorporates recommended target speed and overtaking line into the plan2012 Simulated Car Racing Championship @ CIG-2012
  20. 20. Smile Sheep吳晞浩(Si-Hao Wu)李揚(Yang Lee)李懷哲(Wiser Lee)Advisor: 王才沛(Tsaipei Wang)Taiwan National Chiao Tung University2012 Simulated Car Racing Championship @ CIG-2012
  21. 21. Smile Sheep q  Steering heuristics " drive toward the track sensor with biggest distance " small corection toward middle of the track to avoid borders q  Speed control heuristics " Full accelerating when central sensor is clear for >99m " Slow down when car is too fast q  Recovery policy heuristics " identify stuck condition with heuristics " drive backward and get the car parallel to the track2012 Simulated Car Racing Championship @ CIG-2012
  22. 22. 2012 Simulated Car Racing Championship @ CIG-2012
  23. 23. Mariscal & Fernández q  General approach: expert systems improved by multi- objectives evolutionary computation techniques " Maximize distance. " Minimize damage q  Steering based on a simple rule follow the track sensor with biggest distance. q  Overtaking based on simple rules and expert systems2012 Simulated Car Racing Championship @ CIG-2012
  24. 24. 2012 Simulated Car Racing Championship @ CIG-2012
  25. 25. Ready2Win q  Modular architecture: " Driving module: •  The speed is computed using the maximum braking distance " Overtaking module " Recovery module " ABS module q  Track learning during the warm-up: " First lap, driven slow, to identify turns (start, end, entry position, curvature) and learn the track model " Other laps, speed adaptation: •  Increasing according to lateral speed •  Reducing when the car goes off-road2012 Simulated Car Racing Championship @ CIG-2012
  26. 26. AUTOPIAIndustrial Computer Science Department.Centro de Automática y RobóticaConsejo Superior de Investigaciones CientíficasMadrid, SpainContact:E. Onieva (enrique.onieva@car.upm-csic.es)2012 Simulated Car Racing Championship @ CIG-2012
  27. 27. AUTOPIA q  Fuzzy Architecture based on three basic modules for gear, steering and speed control " optimized with a genetic algorithm q  Learning in the warm-up stage: " Maintain a vector with as many real values as tracklength in meters. " Vector initialized to 1.0 " If the vehicle goes out of the track or suffers damage then multiply vector positions from 250 meters before the current position by 0.95. q  During the race the vector is multiplied by F to make the driver more cautious in function of the damage: " F=1-0.02*round(damage/1000)2012 Simulated Car Racing Championship @ CIG-2012
  28. 28. Qualifying
  29. 29. Scoring process: Warm-up & Qualifying q  Scoring process involves three tracks: " IllSchwang (desert track) " Noceda (city track) " Sehnor (hill track) q  The tracks are not distributed with TORCS: " Generated using the Interactive Track Generator for TORCS and Speed Dreams available at: •  http://trackgen.pierlucalanzi.net " The competitors cannot know the tracks q  Each controller raced for 100000 game ticks in the warm-up stage and then its performance is computed in the qualifying stage as the distance covered within 10000 game ticks2012 Simulated Car Racing Championship @ CIG-2012
  30. 30. Illschwang2012 Simulated Car Racing Championship @ CIG-2012
  31. 31. Qualifying: Ilschwang SmileSheep   7765.42   BFB4   6998.2   Mariscal  &   5066.24   Fernandez   Ready2Win   10010.1   Autopia   10701.6  Ho  Duc  Thang   10808.2   Mr.  Racer   10891.4   0   2000   4000   6000   8000   10000   12000   2012 Simulated Car Racing Championship @ CIG-2012
  32. 32. Noceda2012 Simulated Car Racing Championship @ CIG-2012
  33. 33. Qualifying: Noceda BFB4   9658.8   Mariscal  &   11265.2   Fernandez   Ready2Win   9405.52   AUTOPIA   11648.9  Ho  Duc  Thang   11738.82   Mr.  Racer   12233.2   0   2000   4000   6000   8000   10000   12000   14000   2012 Simulated Car Racing Championship @ CIG-2012
  34. 34. Sehnor2012 Simulated Car Racing Championship @ CIG-2012
  35. 35. Qualifying: Sehnor SmileSheep   8683.94   BFB4   9043.72   Mariscal  &   9610.96   Fernandez   Ready2Win   9413.6   Ho   9646.59   Autopia   10280.7   Mr.  Racer   10483   0   2000   4000   6000   8000   10000   12000  2012 Simulated Car Racing Championship @ CIG-2012
  36. 36. Qualifying summary (scores with noise) Driver Illschwang Noceda Sehnor TotalMr. Racer 10 10 10 30Ho Duc Thang 8 8 6 22AUTOPIA 6 6 8 20Ready2Win 5 3 4 12Mariscal&Fernandez 2 5 5 12BFB4 3 4 3 10SmileSheep 4 2 2 8 CI Approaches2012 Simulated Car Racing Championship @ CIG-2012
  37. 37. What about the qualifying results? Since 2009 AUTOPIA is not the fastest controller for the first time! Top controllers clearly better than others2012 Simulated Car Racing Championship @ CIG-2012
  38. 38. Races
  39. 39. Three Tracks For each track we run 6 races with different starting grids Each race is scored using the F1 point system (10 to first, 8 to second, 6 to third, …) Two points to the controller with lesser damage Two points for the fastest lap of the race2012 Simulated Car Racing Championship @ CIG-2012
  40. 40. Final Results Driver Illschwang Noceda Sehnor Total Autopia 10 12 10 32 Mr. Racer 10 6 10 26 Ready2Win 8 3 6 17 SmileSheep 5 5 5 15 Mariscal&Fernandez 4 6 4 14 BFB4 3 5 4 12 Ho 2 2 2 6 Mr. Racer is winner of SCR@CIG 20122012 Simulated Car Racing Championship @ CIG-2012
  41. 41. What  about  the  race  results?     Qualifying  and  final  results  are  similar:   the  only  excepFon  is  driver  Ho    Some  drivers  were  not  able  to  complete  the   race     Further  analysis  will  be  performed  to  have   more  insight  on  these  results!    
  42. 42. Final  Standings  Championship  CompeGtor Evo* Gecco CIG TotalAUTOPIA   39   35   32   96  Mr.  Racer   16.5   18   26   60.5  Ready2Win   19   20   17   56  Mariscal  &  Fernandez   20   18,5   14   52.5  BFB4   -­‐   11   12   23  Ho  Duc  Thang   -­‐   13   6   19  Smile  Sheep   -­‐   -­‐   15   15  
  43. 43. Final  Standings  Championship  CompeGtor Evo* Gecco CIG TotalAUTOPIA   39   35   32   96  Mr.  Racer   16.5   18   26   60.5  Ready2Win   19   Racer     Mr.   20 17   56  Mariscal  &  Fernandez   WINNER  of     012  S18,5   20 2 14   imulated  Car   52.5  BFB4   Racing  Championship   12   -­‐   11   23  Ho  Duc  Thang   -­‐   13   6   19  Smile  Sheep   -­‐   -­‐   15   15  
  44. 44. We  wait     for     you…   …next  year!   www.geccocompetitions.com info@geccocompetitions.c om @geccocomp /geccocompetitions

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