Self-Driving Car Steering Angle Prediction Based on Image Recognition

TL;DR

This paper explores deep learning models like Transfer Learning, 3D CNN, LSTM, and ResNet to predict steering angles from images for self-driving cars, achieving top-tier performance in a public challenge.

Contribution

It introduces and compares multiple deep learning approaches for steering angle prediction using image data, demonstrating high accuracy and competitive results.

Findings

Models would have ranked in the top ten in the Udacity challenge.

Deep learning techniques effectively predict steering angles from images.

Transfer Learning and ResNet show strong performance.

Abstract

Self-driving vehicles have expanded dramatically over the last few years. Udacity has release a dataset containing, among other data, a set of images with the steering angle captured during driving. The Udacity challenge aimed to predict steering angle based on only the provided images. We explore two different models to perform high quality prediction of steering angles based on images using different deep learning techniques including Transfer Learning, 3D CNN, LSTM and ResNet. If the Udacity challenge was still ongoing, both of our models would have placed in the top ten of all entries.