A deterministic predictive traffic signal control model in intelligent transportation and geoinformation systems
Автор: Myasnikov Vladislav Valerievich, Agafonov Anton Aleksandrovich, Yumaganov Alexander Sergeevich
Журнал: Компьютерная оптика @computer-optics
Рубрика: Численные методы и анализ данных
Статья в выпуске: 6 т.45, 2021 года.
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In this paper, we propose a traffic signal control method in intelligent transportation and geoinformation systems, based on a deterministic predictive model. The method provides adaptive control based on traffic data, including data from connected and autonomous vehicles. The proposed method is compared with the state-of-the-art traffic signal control solutions: empirical control algorithms and reinforcement learning-based control methods. An advantage of the proposed method is shown and directions of further research are outlined.
Data analysis, intelligent transportation system, traffic light control, deterministic model, reinforcement learning, connected and autonomous vehicles
Короткий адрес: https://sciup.org/140290291
IDR: 140290291 | DOI: 10.18287/2412-6179-CO-1031