2012 simulated car racing championship @ evo*-2012

2012 Simulated Car Racing Championship @ evo*-2012

The 2012 Simulated Car Racing Championship @ Evo*-2012Daniele Loiacono, Luigi Cardamone, and Pier Luca Lanzi


2012 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


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, 2012


Motivations

Proposing a relevant game-based competition

more representative of commercial games AI

more similar to a real-world problem

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

Proposing a challenging competition

computationally expensive

real-time

on-line learning

noisy sensors

The Open Racing Car Simulator


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 (with noise)

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


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

Competitors


The competitors

A single entry in this first leg:

Mr. Racer, TU Dortmund

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 Granada


Jan Quadflieg, Tim Delbruegger and Mike Preuss TU Dortmund

Mr Racer


Mr. Racer 2012

Joined effort of Jan Quadflieg, Tim Delbruegger and Mike Preuss

Variables learned offline with the CMA-ES, now including optimized settings for recovery , the clutch and…

NEW: Parameters of the opponent handling module have been optimized

Optimization of the opponent handling will hopefuly result in a CIG competition paper


Noise Handling

1. Low pass filter on sensorvalues

2. 2 Regression polynoms arefitted to each side

3. Resample the polygons

4. Calculate our measure (seeCIG paper 2010)

5. Low pass filter on the last measurements


Online Learning during Warmup

We learn a model of the racetrack

One of two parameter sets is chosen

Target speeds for all corners are then fine tuned

All information is saved at the end of the warmup

And later used during qualifying and the race


Opponent Handling

Noise filtering with a lowpass filter

Observer module interprets filtered sensor readings

This leads to a recommended speed and an overtaking line(created on the fly!)

Planning module incorporates recommended target speedand overtaking line into the plan


Mariscal & Fernández

General approach: expert systems improved by multi-objectives evolutionary computation techniques

Maximize distance.

Minimize damage

Steering based on a simple rule follow thetrack sensor withbiggest distance.

Overtaking based onsimple rules and expertsystems


Ready2Win

Modular architecture:

Driving module:

• The speed is computed using the maximum braking distance

Overtaking module

Recovery module

ABS module

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-road


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)

Qualifying


Scoring process: Warm-up & Qualifying

Scoring process involves three tracks:

Kerang (desert track)

Mueda (city track)

Zvolenovice (mountain track)

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

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

Kerang


Qualifying: Kerang

0 5000 10000 15000

AUTOPIA

Mariscal & Fernandez

Mr. Racer

Ready2Win

NO-NOISY

NOISY

Dirt-1

Mueda


Qualifying: Mueda

0 2000 4000 6000 8000 10000 12000

AUTOPIA


Mr. Racer

Ready2Win NO-NOISY

NOISY

Dirt-1

Zvolenovice


Qualifying: Zvolenovice

6000 6500 7000 7500 8000 8500 9000

AUTOPIA


Mr. Racer

Ready2Win

NO-NOISY

NOISY


Qualifying summary (scores with noise)

Driver Kerang Mueda Zvolenovice Total

AUTOPIA 10 10 6 26

Mr. Racer 6 8 10 24

Ready2Win 8 5 8 21

Mariscal & Fernandez 5 6 5 16


Qualifying summary (scores with noise)

Driver Kerang Mueda Zvolenovice Total

AUTOPIA 10 10 6 26

Mr. Racer 6 8 10 24

Ready2Win 8 5 8 21


Evolutionary Approaches


What about the qualifying results?

AUTOPIA still the fastest controller… …but Mr. Racer is now very close

Almost all the controllers deal very well with noise


Three Tracks

For each track we run 4 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


Competitor Kerang Mueda Zvolenovice Total

AUTOPIA 13 13 13 39


Ready2Win 6 5 8 19

Mr. Racer 5 6 5.5 16.5

Final Results

Next leg @ GECCO-2012 in Philadelphia

What about the race results?

Qualifying and final results are very different

Some drivers were not able to complete the race (even if only 4 cars are on track)

Further analysis will be performed to havemore insight on these results!

Thank you!

SCR Contacts

Official Webpagehttp://games.ws.dei.polimi.it/competitions/scr/

[email protected]

Google Grouphttp://groups.google.com/group/racingcompetition

2012 simulated car racing championship @ evo*-2012

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