Traffic Light Control using Reinforcement Learning: A Survey and an Open Source Implementation

Ciprian Paduraru, Miruna Paduraru, Alin Stefanescu

2022

Abstract

Traffic light control optimization is nowadays an important part of a smart city, given the advancement of sensors, IoT, and edge computing capabilities. The optimization method targeted by our work follows a general trend in the community: dynamically switching traffic light phases depending on the current traffic state. Reinforcement learning was lately adopted in the literature as it has been shown to outperform previous methods. In our literature review, we found a gap in the tools that connect the research area of reinforcement learning with traffic control and simulation environments. Our primary goal in this work is to bridge this technical gap and facilitate the development of both independently. The secondary goal is to provide a state-of-the-art overview of reinforcement methods for the traffic signal control optimization. We also evaluate various algorithms for training policies to compare their performance and efficiency.

Paper Citation

in Harvard Style

Paduraru C., Paduraru M. and Stefanescu A. (2022). Traffic Light Control using Reinforcement Learning: A Survey and an Open Source Implementation. In Proceedings of the 8th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS, ISBN 978-989-758-573-9, pages 69-79. DOI: 10.5220/0011040300003191

in Bibtex Style

@conference{vehits22,
author={Ciprian Paduraru and Miruna Paduraru and Alin Stefanescu},
title={Traffic Light Control using Reinforcement Learning: A Survey and an Open Source Implementation},
booktitle={Proceedings of the 8th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,},
year={2022},
pages={69-79},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011040300003191},
isbn={978-989-758-573-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 8th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,
TI - Traffic Light Control using Reinforcement Learning: A Survey and an Open Source Implementation
SN - 978-989-758-573-9
AU - Paduraru C.
AU - Paduraru M.
AU - Stefanescu A.
PY - 2022
SP - 69
EP - 79
DO - 10.5220/0011040300003191