Pinned Repositories
chd-daka
CHD疫情自动打卡
Comparative-Analysis-of-Reinforcement-Learning-Models-for-Lane-Change-Decision-Making
Researched and compared DQN, Double DQN, and Dueling Double DQN for autonomous vehicle lane changing in Carla simulation. Evaluated performance and collision rates to guide model selection for safer real-world applications. Findings contribute to enhancing autonomous vehicle safety and efficiency.
deep-Q-networks
Implementations of algorithms from the Q-learning family. Implementations inlcude: DQN, DDQN, Dueling DQN, PER+DQN, Noisy DQN, C51
DQN_pytorch
Vanilla DQN, Double DQN, and Dueling DQN implemented in PyTorch
HighwayEnv
A minimalist environment for decision-making in autonomous driving
Lateral-Control
车辆的横向控制
MetaDrive
ShenLanAcademy-PlanningControl
纵向控制：PID ;横向控制：Stanely \ LQR \ MPC
xhfxhfff's Repositories
xhfxhfff/chd-daka
CHD疫情自动打卡
xhfxhfff/Comparative-Analysis-of-Reinforcement-Learning-Models-for-Lane-Change-Decision-Making
Researched and compared DQN, Double DQN, and Dueling Double DQN for autonomous vehicle lane changing in Carla simulation. Evaluated performance and collision rates to guide model selection for safer real-world applications. Findings contribute to enhancing autonomous vehicle safety and efficiency.
xhfxhfff/deep-Q-networks
Implementations of algorithms from the Q-learning family. Implementations inlcude: DQN, DDQN, Dueling DQN, PER+DQN, Noisy DQN, C51
xhfxhfff/DQN_pytorch
Vanilla DQN, Double DQN, and Dueling DQN implemented in PyTorch
xhfxhfff/HighwayEnv
A minimalist environment for decision-making in autonomous driving
xhfxhfff/Lateral-Control
车辆的横向控制
xhfxhfff/MetaDrive
xhfxhfff/ShenLanAcademy-PlanningControl
纵向控制：PID ;横向控制：Stanely \ LQR \ MPC