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Found 6 papers, 1 papers with code
Multi-lane Cruising Using Hierarchical Planning and Reinforcement Learning
Competent multi-lane cruising requires using lane changes and within-lane maneuvers to achieve good speed and maintain safety.
How To Not Drive: Learning Driving Constraints from Demonstration
We propose a new scheme to learn motion planning constraints from human driving trajectories.
Motion Planning for Autonomous Vehicles in the Presence of Uncertainty Using Reinforcement Learning
The approach is evaluated against two challenging scenarios of pedestrians crossing with occlusion and curved roads with a limited field of view.
CoachNet: An Adversarial Sampling Approach for Reinforcement Learning
Despite the recent successes of reinforcement learning in games and robotics, it is yet to become broadly practical.
SMARTS: Scalable Multi-Agent Reinforcement Learning Training School for Autonomous Driving
We open-source the SMARTS platform and the associated benchmark tasks and evaluation metrics to encourage and empower research on multi-agent learning for autonomous driving.
Practical Issues of Action-conditioned Next Image Prediction
Our major finding is that action tiling encoding is the most important factor leading to the remarkable performance of the CDNA model.
