The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/20436090

Ying-Chuan Ni (2022): Source code for the MSc thesis: Multi-leader Adaptive Cruise Control Systems considering Sensor Measurement Uncertainties based on Deep Reinforcement Learning. Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/20436090.v1

Software

• Civil Engineering
• Mechanical Engineering

adaptive cruise control, deep reinforcement learning, Kalman filter, measurement uncertainties, multi-anticipation, ride comfort, string stability

CC0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Ying-Chuan Ni

This repository contains programming codes for the training and simulation of Deep Reinforcement Learning-based Adaptive Cruise Control systems.

For more information, please see the README.txt file in the repository or the report of master thesis titled "Multi-leader Adaptive Cruise Control Systems considering Sensor Measurement Uncertainties based on Deep Reinforcement Learning", which can be found in the reference (link).

• 2022-08-22 first online, published, posted

4TU.ResearchData

Python source code/ .py

• http://resolver.tudelft.nl/uuid%3A08dea442-af73-4b35-b4de-e257287bfc6a

Delft University of Technology, Faculty of Civil Engineering and Geosciences, Department of Transport and Planning.