# Hybrid-DeepRL-Automated-Driving

**Repository Path**: wenb11/Hybrid-DeepRL-Automated-Driving

## Basic Information

- **Project Name**: Hybrid-DeepRL-Automated-Driving
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2025-03-04
- **Last Updated**: 2025-03-04

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# A Hybrid Deep Reinforcement Learning Based Automated Driving Agent for CARLA

Codebase for our Hybrid Deep Reinforcement Learning (H-DRL) based automated driving project.
The related paper can be accessed with [this](https://arxiv.org/pdf/2002.00434.pdf) link.

If you find the code useful for your research, please consider citing our paper:

      @inproceedings{yurtsever2020integrating,
        title={Integrating deep reinforcement learning with model-based path planners for automated driving},
        author={Yurtsever, Ekim and Capito, Linda and Redmill, Keith and Ozguner, Umit},
        booktitle={2020 IEEE Intelligent Vehicles Symposium (IV)},
        pages={1311--1316},
        year={2020},
        organization={IEEE}
      }

> Yurtsever, E., Capito, L., Redmill, K., & Ozguner, U. (2020, June). Integrating deep reinforcement learning with model-based path planners for automated driving. In 2020 IEEE Intelligent Vehicles Symposium (IV) (pp. 1311-1316). IEEE.


## Overview

<img src="gifs/overview.png" title="The proposed method"> 

An overview of our framework. The proposed system is a hybrid of a model-based planner and a model-free DRL agent. *Other sensor inputs can be anything the conventional pipe needs. ** We integrate model-based planners into the DRL agent by adding "distance to the closest waypoint" to our state-space, where the path planner gives the closest waypoint. Furthermore, the reward function is modified accordingly: the agent is penalized for straying away from the model-based planners' waypoints and also making a collision. Any kind of path planner can be integrated into the DRL agent with the proposed method.

## Installation

## Credits
This project was forked from a conventional DRL implementation for CARLA by Sentdex. https://github.com/Sentdex/Carla-RL