AI RESEARCH
Vision-Based Lane Following and Traffic Sign Recognition for Resource-Constrained Autonomous Vehicles
arXiv CS.CV
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ArXi:2604.22872v1 Announce Type: new Autonomous vehicles (AVs) rely on real-time perception systems to understand road environments and ensure safe navigation. However, implementing reliable perception algorithms on resource-constrained embedded platforms remains challenging due to limited computational resources. This paper presents a lightweight vision-based framework that integrates lane detection, lane tracking, and traffic sign recognition for embedded autonomous vehicles.