… Hierarchical Reinforcement Learning (HRL) framework for learning autonomous driving …
We adapt a state-ofthe-art algorithm, Hierarchical Double Deep Q-learning (hDDQN), and …

… Abstract— Behavioral decision making is an important aspect of autonomous vehicles (AV…
hierarchical reinforcement learning (HRL) which is capable of performing autonomous vehicle …

… characteristics of hierarchical reinforcement learning to separate … A policy gradient based
hierarchical reinforcement learning … hierarchical reinforcement learning, how the hierarchical …

… for making hierarchical reinforcement learn- 1 ing practical for autonomous driving on
multi-… While this approach follows the conventional hierarchy of behavior decision, 3 motion …

… and dynamic properties of intelligent vehicles. Aiming at the above problems, this article
proposes a hierarchical reinforcement learning approach for autonomous decision making and …

… and autonomous vehicle rerouting in mixed traffic scenarios where human-driven vehicles
… decentralized bi-directional hierarchical reinforcement learning framework by regarding TLs …

… for racing cars. In this work, A deep reinforcement learning (DRL) with a novel hierarchical
… Hierarchical actions for multi-scale tasks have been actively studied in DRL [12, 27]. [8] …

… on reinforcement learning (RL) which is capable of performing autonomous vehicle behavior
planning with a hierarchical … Application of the hierarchical structure [1] allows the various …

… for an autonomous car using classical reinforcement learning technique known as Q-learning.
We implement the ϵ−greedy algorithm to the problem defined in DeepCars simulation …

… increasingly applying hierarchical reinforcement learning to autonomous driving tasks to …
proposes a novel hierarchical reinforcement learning approach that facilitates the training of sub…