A Sim-to-Real Vision-based Lane Keeping System for a 1:10-scale Autonomous Vehicle

Abstract--In recent years, several competitions have highlighted the need to investigate vision-based solutions to address scenarios with functional insufficiencies in perception, world modeling and localization. This article presents the Vision-based Lane Keeping System (VbLKS) developed by the DEI-Unipd Team within the context of the Bosch Future Mobility Challenge 2022. The main contribution lies in a Simulation-to-Reality (Sim2Real) GPS-denied VbLKS for a 1:10-scale autonomous vehicle. In this VbLKS, the input to a tailored Pure Pursuit (PP) based control strategy, namely the Lookahead Heading Error (LHE), is estimated at a constant lookahead distance employing a Convolutional Neural Network (CNN). Bosch Engineering Center in Cluj (RO), represents a recent addition to this landscape, further strengthened by its collaboration I. Introduction This international technical competition invites teams of students to develop Research on Autonomous Vehicles (AVs) has experienced an autonomous driving algorithms on 1:10 scale vehicles, in an increasingly significant growth of interest in the last few years environment that mimics a miniature smart city (see Figure 1). Anyway, due to its Team within the context of the BFMC 2022, showcasing its complexity, there are still many technical and social challenges pivotal role in the team's victory.