… reinforcement learning based architecture for decision making and control of lane changing
… : 1) when to conduct lane change maneuver and 2) how to conduct the maneuver. To be …

… propose to use a deep reinforcement learning-based method that can learn sub-policies for
… deep reinforcement learning algorithm that can deal with lane change behaviors on road. …

… Through the combination of high-level lateral decision-making and lowlevel rule-based
trajectory modification, a safe and efficient lane change behavior can be achieved. With the …

… reinforcement learning (RL) [11], [12] based lane change. Usually, RL approaches allow an
automated vehicle to gradually learn how … Noticing that frequent lane changing behavior may …

… reinforcement learning based approach to train the agent to learn an automated lane
change behavior … In this paper, deep reinforcement learning algorithms combining with risk …

… Damerow, “Complex lane change behavior in the foresighted driver model,” in 2015 IEEE
18th International Conference on Intelligent Transportation Systems, 2015, pp. 1747–1754. [5] …

… , we proposed a Reinforcement Learning based approach to train the vehicle agent to learn
an automated lane change behavior such that it can intelligently make a lane change under …

… To achieve the first stage, we adopt a polynomial curve to represent the vehicle’s path for
the lane-changing behavior or lane-keeping behavior (see Section IV.B). In the second stage, …

… (PPO)based deep reinforcement learning method, which … lane change behavior based on
deep reinforcement learning,… autonomous lane changing using reinforcement learning,” in …

… of reinforcement learning (RL) [10]. Through trial and error, RL aims to learn the optimal
behavior … Recently, to deal with high-dimensional space problems, deep reinforcement learning (…