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cs.CV2026
Refine Connections, Close the Gap: A Reliable Enhancement Framework for Driving Scene Topology
Xiaoqi Wang, Dingyi Zhaung, Dingyi Zhuang +7
In autonomous driving, understanding scene topology - the connectivity between lanes and traffic elements - is critical for safe path planning and motion control. While current met…
cs.AI2026
Scaling Curriculum Learning For Autonomous Driving
Cevahir Koprulu, David Paz, Feng Tao +4
Batched simulators for autonomous driving have recently enabled training reinforcement learning (RL) agents at scale, encompassing thousands of traffic scenarios and billions of in…
cs.RO2026
Adapting Reinforcement Learning for Path Planning in Constrained Parking Scenarios
Feng Tao, Luca Paparusso, Chenyi Gu +6
Real-time path planning in constrained environments remains a fundamental challenge for autonomous systems. Traditional classical planners, while effective under perfect perception…