Automatic differentiation (AD) can be used to increase speed and accuracy in lap time simulation, widely used in the racing industry, and increasingly in e-sports as this too becomes more competitive and lucrative. NAG's experience within competitive motorsports tells us a successful and performant simulation depends on a range of physical and mathematical models as well as efficient algorithms and tools.
The blog shows some of the ways AD can be used to improve lap simulation, and looks at a case study based on a collaboration with RWTH Aachen University and the Formula Student Team Ecurie Aix. The blog is technical, but we've added some visuals; watch the simulation opposite to see an example of the optimization of lap time simulation using the Silverstone, UK race track.
Read the blog: www.nag.com/blog/increasing-speed-and-accuracy-dynamic-lap-time-simulation-automatic-differentiation