WangZhiDong2000

WangZhiDong2000's Stars

• gustavomoers/E2E-CARLA-ReinforcementLearning-PPO

  An end-to-end (E2E) reinforcement learning model for autonomous vehicle collision avoidance in the CARLA simulator, using a recurrent PPO algorithm for dynamic control. The model processes RGB camera inputs to make real-time acceleration and steering decisions.

  Language:Python91

• omron-sinicx/safe-rover-navi

  The official code respository for "Risk-aware Path Planning via Probabilistic Fusion of Traversability Prediction for Planetary Rovers on Heterogeneous Terrains" (ICRA 2023)

  Language:Jupyter Notebook10

• picchius94/unstruct_navigation

  Utilities to generate random realistic natural terrains, perform traversability analysis, and path planning

  Language:Python41

• SafeRoboticsLab/Safe_Occlusion_Aware_Planning

  Repository for "Safe Occlusion-aware Autonomous Driving via Game-Theoretic Active Perception" - RSS 2021

  Language:Python337

• PuYuuu/vehicle-interaction-decision-making

  The decision-making of multiple vehicles at intersection bases on level-k game and MCTS

  Language:C++6222

• ertsiger/gym-subgoal-automata

  Environments from the papers "Using Reward Machines for High-Level Task Specification and Decomposition in Reinforcement Learning" and "Induction and Exploitation of Subgoal Automata for Reinforcement Learning" using OpenAI Gym API.

  Language:Python97

• BY571/D4PG

  PyTorch implementation of D4PG with the SOTA IQN Critic instead of C51. Implementation includes also the extensions Munchausen RL and D2RL which can be added to D4PG to improve its performance.

  Language:Python164

• WangwangZhu/auto_meta

  Language:C++64

• ayushgoel24/DynamicObstacleAvoidance

  We have compared 4 models- Vanilla LSTM, Social LSTM, OLSTM, and GRU to show their comparison for predicting non linear trajectories of pedestrians in different scenes. We demonstrate their performance on publically available datasets. We show how it is important to take into account the surroundings of the pedestrians to have a better accuracy.

  Language:Jupyter Notebook4

• WangHonghui123/Social-LSTM

  The social-LSTM code for complete trajectory prediction (20 frames). In this repository, the normalized trajectory and non-normalized trajectory are used respectively.

  Language:Python7

• fireblue204/social-LSTM

  复现CVPR2016李飞飞团队提出的轨迹预测网络social-LSTM

  Language:Python3112

• EmreTaha/Social-LSTM-VehicleTrajectory

  Social LSTM using PyTorch for Vehicle Data

  Language:Python11832

• mit-acl/cadrl_ros

  ROS package for dynamic obstacle avoidance for ground robots trained with deep RL

  Language:Python565157

• YoungYoung619/reinforcement-learning-based-driving-decision-in-Carla

  reinforcement learning based agents for self-driving in CARLA

  Language:Python6420

• ghoshavirup0/HighwayENV

  Highway driving simulator incorporating NGSIM dataset using reinforcement learning

  Language:Python485

• Alicia1688/Pedestrian_Crossing_Collision_Risk_Assessment_Datasets

  IESG and Non-IESG datasets

  11

• StanfordVL/STR-PIP

  Spatiotemporal Relationship Reasoning for Pedestrian Intent Prediction

  Language:Python7119

• CHH3213/chhRobotics

  自动驾驶规划控制python代码实现

  Language:Jupyter Notebook463170

• erfanaasi/unmarked_crosswalk_carla_scenario

  Unmarked-crosswalk scenario implemented in CARLA

  2

• willie3838/self-driving-car

  A research project that leverages reinforcement learning and game theory in self-driving cars

  Language:Python151

• mahmoudtaouti/RL_Highway_Merge

  applying multi-agent reinforcement learning for highway-merging autonomous vehicles

  Language:Python401

• kalebbennaveed/Trajectory-Planning-for-Autonomous-Vehicles-Using-HRL

  This file contains code used for a full end-to-end framework for Autonomous Vehicle's lane change using Hierarchical Reinforcement Learning under Noisy Observations

  Language:Python10018

• LoheshM/Comparative-Analysis-of-Reinforcement-Learning-Models-for-Lane-Change-Decision-Making

  Intelligent lane-changing system for autonomous vehicles leveraging Deep Q-Network (DQN), Double DQN, and Dueling Double DQN models in CARLA simulator. Enhances safety and efficiency through informed decision-making in dynamic traffic scenarios.

  Language:Python314

• datvodinh/recurrent-ppo

  A Reinforcement Learning Project using PPO + LSTM

  Language:Python373

• maximilianigl/DVRL

  Deep Variational Reinforcement Learning

  Language:Jupyter Notebook13225

• LinghengMeng/LSTM-TD3

  The implementation of LSTM-TD3.

  Language:Python608

• d3sm0/gym_pomdp

  Gym-like extensions for POMDP

  Language:Python5515

• stweigand/gym-pomdp-wrappers

  POMDP wrappers for OpenAI Gym

  Language:Python151

• marsauto/europilot

  A toolkit for controlling Euro Truck Simulator 2 with python to develop self-driving algorithms.

  Language:Jupyter Notebook1.5k188

• feidieufo/RL-Implementation

  simple code to reinforcement learning

  Language:Python203