E2E Player #3
Advanced AI for Autonomous Racing Simulation
About the Project
E2E Player #3 advances AI racing in BeamNG, building on its predecessor to improve generalization. Our goal is an AI that adapts to new tracks and drives various cars efficiently.
Using an End-to-End (E2E) approach, a neural network processes visual input to determine control outputs—just like a human driver.
The project, named "End-to-End" (E2E), uses a neural network to directly translate visual input into control outputs, mimicking human players who rely solely on screen visuals.
AI vs Human Leaderboard
Lap Time Distribution
Team & Leadership
Ilteris Mete Akdogan
Mujtaba Atai
Ole Brüntrup
Mohammad Nour Dahhan
Florian Feegel
Tobias Fricke
Jost Immoor
Yannick Jess
Dong Hyun (David) Jin
Ben Koch
Joshua Kohls
Firat Kozan
Lukas Kramer
Leonardo Pais Sotgiu
Tim Sperling
Robin Srodka
Thinesh Thiagarajah
E2E Player #3 Team