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Found 5 papers, 1 papers with code
Trajectory Planning for Autonomous Vehicles Using Hierarchical Reinforcement Learning
The problem of incomplete observations is handled by using a Long-Short-Term-Memory (LSTM) layer in the network.
Safe Trajectory Planning Using Reinforcement Learning for Self Driving
Self-driving vehicles must be able to act intelligently in diverse and difficult environments, marked by high-dimensional state spaces, a myriad of optimization objectives and complex behaviors.
Behavior Planning at Urban Intersections through Hierarchical Reinforcement Learning
In this work, we propose a behavior planning structure based on reinforcement learning (RL) which is capable of performing autonomous vehicle behavior planning with a hierarchical structure in simulated urban environments.
Human Driver Behavior Prediction based on UrbanFlow
How autonomous vehicles and human drivers share public transportation systems is an important problem, as fully automatic transportation environments are still a long way off.
Hierarchical Reinforcement Learning Method for Autonomous Vehicle Behavior Planning
In this work, we propose a hierarchical reinforcement learning (HRL) structure which is capable of performing autonomous vehicle planning tasks in simulated environments with multiple sub-goals.
Hierarchical Reinforcement Learning
reinforcement-learning
+2
