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cs.AI2026
Lightweight LiDAR-Based Cone Detection Framework Using Random Forest for Formula Student Driverless
Márk Mező-Kerekes, Péter Praksz, Chang Liu
Reliable, low-latency perception is crucial for Formula Student Driverless vehicles, yet many existing pipelines rely on deep learning and multi-sensor fusion, often requiring GPU…
cs.CV2026
Risk-Aware World Model Predictive Control for Generalizable End-to-End Autonomous Driving
Jiangxin Sun, Feng Xue, Teng Long +4
With advances in imitation learning (IL) and large-scale driving datasets, end-to-end autonomous driving (E2E-AD) has made great progress recently. Currently, IL-based methods have…