A Literature Review of Steering Angle Prediction Algorithms for Autonomous Cars
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Abstract
Road tracking is a critical requirement for the development of autonomous cars. It requires the car to continuously navigate within the designated driving area to avoid any deviation. The computation of steering angles is an essential aspect of achieving autonomous driving. Autonomous steering angle techniques, which are essential for enabling road tracking in autonomous cars, are comprehensively reviewed in this paper. Autonomous steering techniques, mainly involving computer vision methods and end-to-end deep learning approaches, are currently receiving considerable attention. The primary objective of this paper is to identify and reimplement state-of-the-art models in end-to-end deep learning approaches within practical scenarios. We carry out a performance evaluation of each model utilizing real-world tests using scale model cars. Furthermore, we offer perspectives on potential avenues for future research and applications. These may include adaptive modifications to dynamic road conditions, the creation of more effective real-time decision-making algorithms, or the investigation of applications in intricate traffic situations.
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