Self-Driving Car Steering Angle Prediction Based on Image Recognition
This work addresses the critical task of autonomous vehicle control, but it is incremental as it applies existing deep learning methods to a known dataset.
The paper tackled the problem of predicting steering angles for self-driving cars using image recognition on the Udacity dataset, achieving results that would have placed in the top ten of the challenge.
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.