Bayesian Optimization and Deep Learning forsteering wheel angle prediction

Given the current momentum and progress, ADS can be expected to continue to advance as variety of ADS products are going to become commercially available in the space of a decade (Chan, 2017). It is envisioned that automated driving technology will lead to a paradigm shift in transportation systems in terms of user experience, mode choices and business models. Nowadays, a greater number of industrialists are increasing their investments in self-driving cars technologies and, more generally, in the automotive sector. ADS research and an increasing number of industrial implementations have been catalyzed by the accumulated knowledge in vehicle dynamics in the wake of breakthroughs in computer vision caused by the advent of deep learning (Krizhevsky, Sutskever, and Hinton, 2012; Bojarski, Yeres, Choromanaska, Choromanski, Firner, Jackel, and Muller, 2017; Kocić, Jovičić, and Drndarević, 2019; Li, Yang, Qu, Cao, and Li, 2021a) and the availability of new sensor modalities such as lidar (Schwarz, 2010). Deep Learning (DL) has been widely used for the implementation of ADSs.