A deterministic predictive traffic signal control model in intelligent transportation and geoinformation systems
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 com...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Samara National Research University
2021-12-01
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| Series: | Компьютерная оптика |
| Subjects: | |
| Online Access: | https://computeroptics.ru/eng/KO/Annot/KO45-6/450616e.html |
| _version_ | 1797869300279672832 |
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| author | V.V. Myasnikov A.A. Agafonov A.S. Yumaganov |
| author_facet | V.V. Myasnikov A.A. Agafonov A.S. Yumaganov |
| author_sort | V.V. Myasnikov |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-10T00:09:21Z |
| format | Article |
| id | doaj.art-dfe97a4bfa9d44a894ab9ace5bec5f1c |
| institution | Directory Open Access Journal |
| issn | 0134-2452 2412-6179 |
| language | English |
| last_indexed | 2024-04-10T00:09:21Z |
| publishDate | 2021-12-01 |
| publisher | Samara National Research University |
| record_format | Article |
| series | Компьютерная оптика |
| spelling | doaj.art-dfe97a4bfa9d44a894ab9ace5bec5f1c2023-03-16T14:19:54ZengSamara National Research UniversityКомпьютерная оптика0134-24522412-61792021-12-0145691792510.18287/2412-6179-CO-1031A deterministic predictive traffic signal control model in intelligent transportation and geoinformation systemsV.V. Myasnikov0A.A. Agafonov1A.S. Yumaganov2Samara National Research University; IPSI RAS – Branch of the FSRC "Crystallography and Photonics" RASSamara National Research UniversitySamara National Research UniversityIn 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.https://computeroptics.ru/eng/KO/Annot/KO45-6/450616e.htmlimage segmentationroad pavement distresssynthetic datasetgenerative adversarial networkconvolutional neural network |
| spellingShingle | V.V. Myasnikov A.A. Agafonov A.S. Yumaganov A deterministic predictive traffic signal control model in intelligent transportation and geoinformation systems Компьютерная оптика image segmentation road pavement distress synthetic dataset generative adversarial network convolutional neural network |
| title | A deterministic predictive traffic signal control model in intelligent transportation and geoinformation systems |
| title_full | A deterministic predictive traffic signal control model in intelligent transportation and geoinformation systems |
| title_fullStr | A deterministic predictive traffic signal control model in intelligent transportation and geoinformation systems |
| title_full_unstemmed | A deterministic predictive traffic signal control model in intelligent transportation and geoinformation systems |
| title_short | A deterministic predictive traffic signal control model in intelligent transportation and geoinformation systems |
| title_sort | deterministic predictive traffic signal control model in intelligent transportation and geoinformation systems |
| topic | image segmentation road pavement distress synthetic dataset generative adversarial network convolutional neural network |
| url | https://computeroptics.ru/eng/KO/Annot/KO45-6/450616e.html |
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