Forum for Science, Industry and Business

Sponsored by:     3M 
Search our Site:

 

Survival of the fastest: scientists ’selectively breed’ winning Formula One cars

17.06.2004


Speed is the name of the game in the world of racing and now UCL scientists have developed a technique that ’breeds’ winning Formula One cars.



By applying Darwinian principles to the art of motor racing, the researchers demonstrate in simulations that it’s possible to knock crucial tenths of a second off lap time by tailoring a car’s setup to whatever conditions are faced on the track.

In a paper to be presented later this month at a conference in Seattle, researchers will report on a new computer model based on genetic algorithms that optimises performance by selectively combining the best settings of Formula One cars to produce the ultimate configuration.


Results show it’s possible to shave 0.88 of a second per lap from the best time. In an industry where 1/100th of a second can separate a winner from a loser, that can make all the difference.

Dr. Peter Bentley, leader of the Digital Biology Group at UCL’s Department of Computer Science and senior author of the study, says:

"Formula One spends millions each year designing and applying the latest technology to ensure their cars can handle whatever is thrown at them on the track. Each car can be modified in hundreds of way to optimise performance. Even minor changes in wing height, suspension stiffness or type of tyre rubber are ’tweaked’ to give them the competitive edge.

"Before every race, attempts are made to optimise settings for given conditions but cars are so finely calibrated than even subtle changes in temperature can affect performance. Decisions are based on experience but there are no guarantees they will always get it right.

"By running simulations we were able to distinguish how different facets of the car perform. Each best performance solution was treated as though it had its own genes that define those parameters. These winning solutions were then bred to produce the next generation, which combined the best settings of both parent cars until eventually we evolved the ultimate Formula One vehicle setup."

Genetic algorithms are an emerging technology that unites the fields of biology and computer science by mimicking the process of evolution in computers in an effort to find the best solutions to complex problems. A number of possible solutions to the problem are treated as ’organisms’ known as phenotypes. These are placed into a simulated environment, allowing them to be judged by a set of conditions. Only the better phenotypes survive and they produce ’children’ in the next generation. These children are then judged in the environment, the better ones have children, and so on. After a number of generations have passed, fitter phenotypes evolve with new forms better suited to the task required.

The researchers configured 68 parameters in the simulation car, which affected suspension, the engine, tyre and brake pressure, fuel consumption and steering control. Variables included:


anti-sway – has an effect on the under/over-steer for the car and the contact that the tyres have with the ground
gear ratios – effects the acceleration of the car
wings – change the downwards force of the vehicle and its grip on the road
Five experiments were performed using a racing simulation designed by Electronic Arts. The first four experiments tested the car on the UK’s Silverstone track. Population size and the number of generations were varied to determine the effect on optimisation. The final run was tested on Germany’s Nurburgring track to assess whether the evolved car could still be a winner on a track that presented different challenges.

Mr. Krzysztof Wloch, of UCL’s Department of Computer Science and lead author of the study, explains:

"Silverstone is generally a fast circuit with several slow corners and a selection of fast sweeping turns. This allowed us to test cars that are tuned for higher speed, with less down force for cornering. In contrast Nurburgring is a very twisty and tough track. That means cars need to be configured for high-down force to handle tight corners at speed."

At Silverstone, lap time was improved from 1 minute 27.005 seconds to 1 minute 21.050 seconds. Similarly, optimal lap time at Nurburgring improved by seven per cent.

To verify results, a virtual race was set up at Silverstone using cars configured using: genetic algorithms; the default settings of the simulator; human tuning; and an Internet expert. Results placed the evolved setting first with a time of 1 minute 20.349 seconds. The expert setting came second, 0.879 seconds slower. The human tuning came third with a time 1.09 seconds slower. The default settings came last, a massive 2.42 seconds behind. In real life, the fastest lap for Silverstone in 2003 was 1 minute 21.209 seconds.

"The real test would be to use our system in an actual Formula One car," says Dr Bentley. "At present have they have their own software that monitors performance during a race. Using our system you could evolve the car setup while the racing is going on. So if a car was damaged, at the next pit stop you could optimise the settings to offset whatever has gone wrong. You could even beam changes to the car while it is on the track, but somehow I don’t think racing authorities would go for that."

Details of the study will also appear in this week’s New Scientist magazine (19/06/04).


For further information please contact
Judith H. Moore
Media Relations Manager
University College London
Tel: 44-0-20-7679-7678
Mobile: 44-0-77-3330-7596
Email: judith.moore@ucl.ac.uk

Judith H Moore | EurekAlert!
Further information:
http://www.ucl.ac.uk/

All articles from Information Technology >>>

The most recent press releases about innovation >>>

Die letzten 5 Focus-News des innovations-reports im Überblick:

Im Focus: Successfully Tested in Praxis: Bidirectional Sensor Technology Optimizes Laser Material Deposition

The quality of additively manufactured components depends not only on the manufacturing process, but also on the inline process control. The process control ensures a reliable coating process because it detects deviations from the target geometry immediately. At LASER World of PHOTONICS 2019, the Fraunhofer Institute for Laser Technology ILT will be demonstrating how well bi-directional sensor technology can already be used for Laser Material Deposition (LMD) in combination with commercial optics at booth A2.431.

Fraunhofer ILT has been developing optical sensor technology specifically for production measurement technology for around 10 years. In particular, its »bd-1«...

Im Focus: The hidden structure of the periodic system

The well-known representation of chemical elements is just one example of how objects can be arranged and classified

The periodic table of elements that most chemistry books depict is only one special case. This tabular overview of the chemical elements, which goes back to...

Im Focus: MPSD team discovers light-induced ferroelectricity in strontium titanate

Light can be used not only to measure materials’ properties, but also to change them. Especially interesting are those cases in which the function of a material can be modified, such as its ability to conduct electricity or to store information in its magnetic state. A team led by Andrea Cavalleri from the Max Planck Institute for the Structure and Dynamics of Matter in Hamburg used terahertz frequency light pulses to transform a non-ferroelectric material into a ferroelectric one.

Ferroelectricity is a state in which the constituent lattice “looks” in one specific direction, forming a macroscopic electrical polarisation. The ability to...

Im Focus: Determining the Earth’s gravity field more accurately than ever before

Researchers at TU Graz calculate the most accurate gravity field determination of the Earth using 1.16 billion satellite measurements. This yields valuable knowledge for climate research.

The Earth’s gravity fluctuates from place to place. Geodesists use this phenomenon to observe geodynamic and climatological processes. Using...

Im Focus: Tube anemone has the largest animal mitochondrial genome ever sequenced

Discovery by Brazilian and US researchers could change the classification of two species, which appear more akin to jellyfish than was thought.

The tube anemone Isarachnanthus nocturnus is only 15 cm long but has the largest mitochondrial genome of any animal sequenced to date, with 80,923 base pairs....

All Focus news of the innovation-report >>>

Anzeige

Anzeige

VideoLinks
Industry & Economy
Event News

SEMANTiCS 2019 brings together industry leaders and data scientists in Karlsruhe

29.04.2019 | Event News

Revered mathematicians and computer scientists converge with 200 young researchers in Heidelberg!

17.04.2019 | Event News

First dust conference in the Central Asian part of the earth’s dust belt

15.04.2019 | Event News

 
Latest News

A new force for optical tweezers awakens

19.06.2019 | Physics and Astronomy

New AI system manages road infrastructure via Google Street View

19.06.2019 | Information Technology

A new manufacturing process for aluminum alloys

19.06.2019 | Materials Sciences

VideoLinks
Science & Research
Overview of more VideoLinks >>>