Tuning path tracking controllers for autonomous cars using reinforcement learning

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PeerJ Computer Science

Main article text

 

Introduction

Implementation

Low-level controller

The simulator

High-level supervisor

Reinforcement learning agent

Simulation Results

An argument on dependability

Conclusions

Additional Information and Declarations

Competing Interests

The authors declare there are no competing interests.

Author Contributions

Ana Vilaça Carrasco conceived and designed the experiments, performed the experiments, analyzed the data, performed the computation work, prepared figures and/or tables, authored or reviewed drafts of the article, and approved the final draft.

João Silva Sequeira conceived and designed the experiments, analyzed the data, authored or reviewed drafts of the article, worked out the technical arguments supporting the dependability of the whole architecture, and approved the final draft.

Data Availability

The following information was supplied regarding data availability:

The software is available at GitHub and Zenodo:

- https://github.com/anavc97/RL-for-Autonomus-Vehicles

- anavc97. (2023). anavc97/RL-for-Autonomus-Vehicles: v1.0.0 (05.2023). Zenodo. https://doi.org/10.5281/zenodo.8078645.

Funding

This research was supported by FCT projects LARSyS LA/P/0083/2020 and UIDB/P/50009/2020. There was no additional external funding received for this study.

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