End2Race: An End-to-End Learning Framework for Multi-Vehicle Autonomous Racing

arXiv:2509.16894 · cs.RO · Submitted 2025-09-21 · Read on arXiv

cs.RO

Submitted: 2025-09-21

Updated: 2026-09-16

Code: https://github.com/michigantraffic-lab/End2Race

Terminology

• Reinforcement Learning — 8× in this paper · explained in 4 episodes
• Steering — 7× in this paper · explained in 2 episodes
• Actor — 4× in this paper · explained in 3 episodes
• Transformer — 4× in this paper · explained in 2 episodes
• Behavioral Cloning — 3× in this paper
• Proximal Policy Optimization — 3× in this paper
• Ablation — 2× in this paper · explained in 1 episode
• Ablation study — 2× in this paper · explained in 1 episode
• Adaptation — 2× in this paper · explained in 1 episode
• Benchmark — 2× in this paper · explained in 2 episodes
• Deep Reinforcement Learning — 2× in this paper · explained in 2 episodes
• Gated Recurrent Unit — 2× in this paper
• Adam — 1× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Distribution Shift — 1× in this paper · explained in 6 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• IEEE Intelligent Vehicles Symposium — 1× in this paper
• IEEE International Conference on Robotics and Automation — 1× in this paper
• Imitation Learning (IL) — 1× in this paper · explained in 2 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Model Predictive Control (MPC) — 1× in this paper · explained in 5 episodes
• Online Adaptation — 1× in this paper · explained in 3 episodes
• Proximal Policy Optimization (PPO) — 1× in this paper · explained in 5 episodes
• Regret — 1× in this paper · explained in 3 episodes
• Reward Function — 1× in this paper · explained in 2 episodes
• Sample Efficiency — 1× in this paper · explained in 4 episodes
• Zero-Shot Transfer — 1× in this paper · explained in 4 episodes

Sources

• CDDT: Fast Approximate 2D Ray Casting for Accelerated Localization
• TinyLidarNet: 2D LiDAR-based End-to-End Deep Learning Model for F1TENTH Autonomous Racing
• Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
• Hardware Neural Control of CartPole and F1TENTH Race Car
• Dream to Control: Learning Behaviors by Latent Imagination
• Track based Offline Policy Learning for Overtaking Maneuvers with Autonomous Racecars
• Proximal Policy Optimization Algorithms
• Bridging the Gap between Discrete Agent Strategies in Game Theory and Continuous Motion Planning in Dynamic Environments
• PythonRobotics: a Python code collection of robotics algorithms

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