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IEEE2d
Intention-Guided Heuristic Partially Observable Monte Carlo Planning for Off-Ramp Decision-Making of Autonomous Vehicles - IEEE Xplore
The Partially Observable Monte Carlo Planning (POMCP) leverages Monte Carlo Tree Search (MCTS) and Particle Filtering (PF) to enhance the computational efficiency in solving large-scale Partially ...
IEEE4d
To Cooperate or Not: Multi-Agent Reinforcement Learning-Based On-Ramp Merging Strategies for Autonomous Vehicles - IEEE Xplore
On-ramp merging for Autonomous Vehicles (AVs) is a challenging task that involves complex interactions of multiple vehicles and should consider both the safety and efficiency. Extensive works have ...