2010 Simulated Car Racing Championship @ CIG-2010

2010 Simulated Car Racing Championship @ CIG-2010

The 2010 Simulated Car Racing

Championship @ CIG-2010Daniele Loiacono, Luigi Cardamone,

Martin V. Butz, and Pier Luca Lanzi


2010 Simulated Car Racing Championship9 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 scorewins the championship

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The 2010 Simulated Car Racing Championship

GECCO-2010Portland , July 7-11American LegWinner: Autopia

WCCI-2010Barcelona, July 18-23Formula LegWinner: Jorge Muñoz

CIG-2010Copenhagen, August 18–21Dusty LegWinner: ???


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 together

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What’s new?

If everything seems under control, you're not going fast enough— Mario Andretti

Warm-up stage

Before qualifying stage, competitors have 100000 game ticks to race on the track

Allows track learning and optimization of parameters

Noisy sensors

Track sensors and opponent sensors are affected by a Gaussian noise (standard deviation equal to 10% of the readings)

Extended sensor model

Focus sensors

Z position and speed

Direction of track sensors fully customizable

Added clutch control and focus command

The Open Racing Car Simulator


The Open Racing Car Simulator

TORCS is a state of the art open source simulator written in C++

Main features

Sophisticated dynamics

Provided with several cars, tracks, and controllers

Active community of users and developers

Easy to develop your own controller

OS Support

Linux: binaries and building from sources

Windows: binaries and “limited” bulding from sources support

OSX: legacy binaries and no building from sources support


The Open Racing Car Simulator & the Competition Software

TORCS

BOT BOT BOT

TORCS

PATCH

SBOT SBOT SBOT

BOT BOTBOT

UDP UDPUDP The competition server

Separates the bots from TORCS

Build a well-defined sensor model

Works in real-time


Sensors and actuators

Rangefinders for edges on the track and opponents

Speed, RPM, fuel, damage, angle with track, distance race, position on track, etc.

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 direction

Competitors


The competitors

Five entries in the second leg

AUTOPIA, Madrid and Granada

J. Muñoz, Carlos III University of Madrid

S.Pohl, J. Quadflieg and T. Delbrügger, TU Dortmund

Joseph Alton, University of Birmingham

Timothy Alford (Xiaodong Li), RMIT University, Melbourne

Neil Clarke, University of Birmingham

Two more entries from the 2009 championship

COBOSTAR (T. Lönneker & M.V. Butz, University ofWürzburg)

POLIMI (Cardamone, Politecnico di Milano)


Industrial Computer Science Department.

Centro de Automática y Robótica

Consejo Superior de Investigaciones Científicas

Madrid, Spain

Contact:E. Onieva ([email protected])

AUTOPIA


AUTOPIA

Fuzzy Architecture based on three basic modules for gear, steering and speed control

optimized with a genetic algorithm

Learning in the warm-up stage:

Maintain a vector with as many real values as tracklengthin 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.

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)


Susanna Pohl, Jan Quadflieg and Tim DelbrüggerTU Dortmund

Mr Racer


Mr. Racer

Save the model after warm-up, use it during qualifying and the race

The track model is built using a classifier

Use the model to derive a plan consisting of target speeds and a racing line

Unfortunately the noisy completelybreaks the classifier


Department of Computer ScienceCarlos III University of Madrid

Jorge Muñoz


Jorge Muñoz

Build a model of the track during the warm-up stage.

Two neural networks to predict the trajectory using the track model. Two neural networks to predict the target speed given the model of the track and the current car position

The four neural networks are trained with backpropagation using data retrieved from a human player

Learning during the warm-up:

The car remember where it goes out of the car or drives far form the trajectory and in the next laps goes slower in those points

The car remember where it follows the trajectory perfectly and tries to go faster in the next laps.


Joseph Alton

Joseph Alton


Joseph Alton

Scripted controller

During warm-up the controller drives with a fixed speed of 60 km/h

During this time for each segment (meter) of the track, the turns are recorded and mapped to a speed.

The speeds are as follows:

Noise filtering is done through having multiple sensors at the same position

Type Value Speed ( km/h)

Sharp turn > Absolute 0.1 60

Turn > Absolute 0.05 100

Straight 200


Timothy Alford (supervised by Xiaodong Li)

RMIT University, Melbourne, Victoria


Tim Alford

Y

N

Action object

Action object

on track ?

Recovery

Fuzzy system

Gears

Sensors

All components of the car are controlled by Fuzzy Logic (excluding gears and recovery )

Recovery, Gears are controlled with simple rules

GA is exploited in the Warm-up


Timothy Alford (supervised by Xiaodong Li)

RMIT University, Melbourne, VictoriaNeil ClarkeUniversity of Birmingham


Neil Clarke

Controller based on a Feed Forward Multi Layer Neural Network

Imitation Leaning

Trained using the human data provided by the author

Very simple policy for the opponents


COBOSTAR

Thies Lönneker and Martin V. Butz

University of Würzburg

http://www.coboslab.psychologie.uni-wuerzburg.de


COBOSTAR

One of the best controller of the 2009 Championship

Parameterized controller optimized with CMA-ES

Dynamically saves crash points


CIG-2008 Champ

Luigi Cardamone

Politecnico di Milano


Luigi Cardamone

Winner of the CIG-2008 Car Simulated Competition

The controller is based on a neural network evolved with NEAT

Very simple policy for overtaking

Qualifying


Scoring process: Warm-up Qualifying

Scoring process involves three dirt tracks:

Dirt-1

Olethros-Dirt

Rocky

Only the track Dirt-1 is provided with TORCS distribution:

Olethros-Dirt was created adding the sand to the original track Olethros

Rocky is an evolved track

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 ticks


Dirt-1


Qualifying: Dirt-1

6125,74

4851,54

2665,89

5340,37

5218,73

4168,25

5696,28

2291,56

0 1000 2000 3000 4000 5000 6000 7000

Autopia

Jorge Muñoz

Joseph Alton

Cardamone

COBOSTAR

MR. Racer

Neil Clarke

Timothy Alford


Olethros-Dirt


Qualifying: Olethros-Dirt

6988,33

2292,59

0

5024,56

6285,36

2352,1

2135,18

3176,7

0 1000 2000 3000 4000 5000 6000 7000 8000

Autopia

Jorge Muñoz

Joseph Alton

Cardamone

COBOSTAR

MR. Racer

Neil Clarke

Timothy Alford


Rocky


6177,81

4437,02

0

5881,37

6409,76

2736,39

2261,45

1971,52

0 1000 2000 3000 4000 5000 6000 7000

Autopia

Jorge Muñoz

Joseph Alton

Cardamone

COBOSTAR

MR. Racer

Neil Clarke

Timothy Alford

Qualifying: Rocky


Qualifying summary

Dirt-1 Olethros-dirt Rocky Total

Autopia10 10 8 28

Cardamone5 8 10 23

COBOSTAR6 6 6 18

Neil8 2 3 13

Mr. Racer4 3 5 12

Tim3 4 4 11

Jorge Muñoz1 5 2 8

Joseph Alton*2 1 1 4

Joseph Alton was disqualified from the race as crashes in 2 over 3 tracks

What about qualifying?

AUTOPIA is the fastest driver

Also, Cardamone (a very old driver ) did very well

For some drivers noise seems to affect significantly the performance

However, some controllers are able to reach almost the same performance even with noise


How much does noise affect the performance?


Dirt-1 with and without noise

6125,74

4851,54

2665,89

5340,37

5218,73

4168,25

5696,28

2291,56

6201,71

4966,6

2666,12

5404,24

5380,04

5097,69

6204,14

1707,26

0 1000 2000 3000 4000 5000 6000 7000

Autopia

Jorge Muñoz

Joseph Alton

Cardamone

COBOSTAR

MR. Racer

Neil Clarke

Timothy Alford

NO-NOISY NOISY

The Race


Three Tracks

For each track we run 7 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 race

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Race: Dirt-1

Competitor Score

Cardamone 10

Autopia 8

COBOSTAR 8

Neil 7

Jorge Muñoz 4

Tim 4

Mr. Racer 3


Race: Olethros-dirt

Competitor Score

Autopia12

COBOSTAR8

Cardamone6

Tim6

Neil5

Mr. Racer4

Jorge Muñoz2


Race: Rocky

Competitor Score

COBOSTAR8

Cardamone8

Mr. Racer8

Jorge Muñoz6

Autopia5

Neil4

Tim3


Final Results

Competitor Dirt-1 Ole-Dirt Rocky Total

Autopia 8 12 5 25

Cardamone 10 6 8 24

COBOSTAR 8 8 8 24

Neil 7 5 4 16

Mr. Racer 3 4 8 15

Tim 4 6 3 13

Jorge Muñoz 4 2 6 12


Final Standings

Competitor GECCO WCCI CIG Total

AUTOPIA 34 24 25 83

COBOSTAR 14 28 24 66

Jorge Muñoz 22.5 28 12 62.5

Cardamone 16 16 24 56

Mr. Racer 16 9 15 40

Joseph Alton 15.5 11 - 26.5

Tim Alford - 10 13 23

Neil Clarke - - 16 16


The 2010 Simulated Car Racing Championship

GECCO-2010Portland , July 7-11American LegWinner: Autopia

WCCI-2010Barcelona, July 18-23Formula LegWinner: Jorge Muñoz

CIG-2010Copenhagen, August 18–21Dusty LegWinner: Autopia


Analysis of results

Competitor GECCO WCCI CIG

AUTOPIA 34 24 25

COBOSTAR 14 28 24

Jorge Muñoz 22.5 28 12

Cardamone 16 16 24

Mr. Racer 16 9 15

Joseph Alton 15.5 11 -

Tim Alford - 10 13

Neil Clarke - - 16


Analysis of results

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2

3

4

5

6

7

8

GECCO WCCI CIG

AUTOPIA

COBOSTAR

Jorge Muñoz

Cardamone

Mr. Racer


What about new challenges?

Noisy sensors

Addressed by almost all the competitors

For most of the approaches is critical only for opponent management

Still an open problem

Warm-up stage

Addressed by almost all the competitors

Simple on-line adaptation (e.g., list of crash points implemented in COBOSTAR) still very competitive

We expect big improvements in this task in the future

Custom Rangefinders Setup and Clutch Control


Conclusions

Car Racing Community

Overall 6 competitors entered the competition (last year we got 11 entries)

Almost the same authors in the first positions

New competitors enter for a while and leave

Do not be scared

The source of entries will be available on-line

A lot of opportunities to improve the current controllers

2010 Simulated Car Racing Championship @ CIG-2010

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