|
This article is cited in 9 scientific papers (total in 9 papers)
NUMERICAL METHODS AND DATA ANALYSIS
A deterministic predictive traffic signal control model in intelligent transportation and geoinformation systems
V. V. Myasnikovab, A. A. Agafonova, A. S. Yumaganova a Samara National Research University
b Image Processing Systems Institute of the RAS - Branch of the FSRC "Crystallography and Photonics" RAS, Samara, Russia, Samara
Abstract:
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.
Keywords:
data analysis, intelligent transportation system, traffic light control, deterministic model, reinforcement learning, connected and autonomous vehicles
Received: 25.08.2021 Accepted: 07.09.2021
Citation:
V. V. Myasnikov, A. A. Agafonov, A. S. Yumaganov, “A deterministic predictive traffic signal control model in intelligent transportation and geoinformation systems”, Computer Optics, 45:6 (2021), 917–925
Linking options:
https://www.mathnet.ru/eng/co983 https://www.mathnet.ru/eng/co/v45/i6/p917
|
Statistics & downloads: |
Abstract page: | 22 | Full-text PDF : | 10 |
|