Adaptive Traffic Control Using Cooperative Communication Through Visible Light

被引:0
|
作者
Vieira M.A. [1 ,2 ]
Vieira M. [1 ,2 ]
Louro P. [1 ,2 ]
Vieira P. [1 ,4 ]
Fernandes R. [1 ]
机构
[1] Electronics Telecommunications and Computer Department, ISEL/IPL, Lisbon
[2] UNINOVA-CTS and LASI, Lisbon
[3] NOVA School of Science and Technology, Lisbon
[4] Instituto de Telecomunicações, IST, Lisbon
关键词
Deep reinforcement learning model; Light controlled intersection; Queue distance; Traffic control; Vehicular communication; Mesh/cellular” hybrid network;
D O I
10.1007/s42979-023-02483-9
中图分类号
学科分类号
摘要
The study aims to create a Visible-Light Communication (VLC) system for secure vehicle management at intersections. This involves enabling communication between vehicles and infrastructure (V2V, V2I, and I2V) using headlights, streetlights, and traffic signals. Mobile optical receivers gather data, determine their location, and read transmitted information through joint transmission. An intersection manager coordinates traffic and communicates with vehicles through embedded Driver Agents. The system utilizes a "mesh/cellular" hybrid network configuration and encodes data into light signals emitted by transmitters. Optical sensors and filtering properties enable reception and decoding. The study demonstrates bidirectional communication, employing queue/request/response mechanisms and relative pose concepts for safe vehicle passage. A deep reinforcement learning model controls traffic light cycles, validated via simulation in a Simulation of Urban Mobility simulator. Results show that this adaptive traffic control system effectively collects detailed vehicle data and ensures secure communication within the short-range mesh network. © 2024, The Author(s).
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