# Experiments in Autonomous Driving Through Imitation Learning

arXiv: https://arxiv.org/abs/2011.12460 · HTML: https://mlsanity.com/paper/2011.12460/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Placed in Imitation and offline RL for driving, one of 13 directions in Offline RL and imitation learning from data.
- Builds on 1 of its 5 references that are in the map.
- First posted on arXiv 25 Nov 2020.

## Placed in

- Offline RL and imitation learning from data / [Imitation and offline RL for driving](https://mlsanity.com/offlinerl/imitation-and-offline-rl-for-driving/)

## Builds on (most cited first, 1 of 1)

- [Fooling a Real Car with Adversarial Traffic Signs](https://mlsanity.com/paper/1907.00374/) (2019)

## Abstract (arXiv)

This report demonstrates several methods used to make a self-driving vehicle using a supervised learning algorithm and a forward-facing RGBD camera. The project originally involved research in creating an adversarial attack on the vehicle's model, but due to difficulties with the initial training of the car, the plans were discarded in favor of completing the imitation learning portion of the project. Many approaches were explored, but due to challenges introduced by an unbalanced data set, the approaches had limited effectiveness.