KB-Tree: Learnable and Continuous Monte-Carlo Tree Search for Autonomous Driving Planning
Lanxin Lei,Ruiming Luo,Renjie Zheng,Jingke Wang,JianWei Zhang,Cong Qiu,Liulong Ma,Liyang Jin,Ping Zhang,Junbo Chen,Lanxin Lei,Ruiming Luo,Renjie Zheng,Jingke Wang,JianWei Zhang,Cong Qiu,Liulong Ma,Liyang Jin,Ping Zhang,Junbo Chen
In this paper, we present a novel learnable and continuous Monte-Carlo Tree Search method, named as KB-Tree, for motion planning in autonomous driving. The proposed method utilizes an asymptotical PUCB based on Kernel Regression (KR-AUCB) as a novel UCB variant, to improve the exploitation and exploration performance. In addition, we further optimize the sampling in continuous space by adapting Ba...
