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Traffic Signal Control System Using Contour Approximation Deep Q-Learning †.
- Source :
- Engineering Proceedings; 2024, Vol. 62, p19, 7p
- Publication Year :
- 2024
-
Abstract
- A reliable transit system is essential and offers a lot of advantages. However, traffic has always been an issue in major cities, and one of the main causes of congestion in these places is intersections. To reduce traffic, a reliable traffic control system must be put in place. This research sheds light on how to consider dynamic traffic at intersections and minimize traffic congestion using an end-to-end deep reinforcement learning approach. The goal of the model is to reduce waiting times at these crossings by controlling traffic in various scenarios after receiving the necessary training. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 26734591
- Volume :
- 62
- Database :
- Complementary Index
- Journal :
- Engineering Proceedings
- Publication Type :
- Academic Journal
- Accession number :
- 180070637
- Full Text :
- https://doi.org/10.3390/engproc2024062019