| Issue |
EPJ Web Conf.
Volume 305, 2024
6th International Conference on Applications of Optics and Photonics (AOP2024)
|
|
|---|---|---|
| Article Number | 00030 | |
| Number of page(s) | 6 | |
| DOI | https://doi.org/10.1051/epjconf/202430500030 | |
| Published online | 23 October 2024 | |
https://doi.org/10.1051/epjconf/202430500030
Enhancing Urban Traffic Management with Visible Light Communication and Reinforcement Learning
1 Electronics Telecommunications and Computer Dept. ISEL/IPL, R. Conselheiro Emídio Navarro, 1949-014 Lisboa, Portugal.
2 CTS-UNINOVA and LASI, Monte da Caparica, 2829-516, Caparica, Portugal
3 INESC INOV-Lab, Lisboa, Portugal
Published online: 23 October 2024
This paper introduces Visible Light Communication (VLC) to enhance traffic signal efficiency and vehicle trajectory management at urban intersections. A multi-intersection traffic control system is proposed, integrating VLC localization services with learning-based traffic signal control. VLC facilitates communication between connected vehicles and infrastructure using headlights, streetlights, and traffic signals to transmit information. By leveraging vehicle-to-vehicle (V2V) and infrastructure-to-vehicle (I2V) interactions, joint transmission and data collection are achieved via mobile optical receivers. The system aims to reduce waiting times for pedestrians and vehicles while improving overall traffic safety. It is designed to be flexible and adaptive, accommodating diverse traffic movements during multiple signal phases. VLC cooperative mechanisms, transmission range, relative pose concepts, and queue/request/response interactions help balance traffic flow between intersections, enhancing the overall road network performance.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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