Steering Angle Prediction for Autonomous Cars Based on Deep Neural Network Method

Jian Zhang, Hailong Huang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review


A huge influx of interest and funding is supporting advances in autonomous vehicles. This paper employs deep neural networks to extract features from images taken from cameras mounted on the left, right, and center of the front windshield. The synthetic images used in our work are generated from the Udacity platform, which is an open-source simulator developed based on Unity. We find that the features learned can be beneficial to the task of steering prediction. The proposed model has been experimentally verified in several environments. We use the desert environment as the training set and use the desert and mountain environments as the test set.
Original languageEnglish
Title of host publication2020 Australian and New Zealand Control Conference (ANZCC)
Publication statusPublished - Nov 2020

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