A Study of Artificial Neural Network-Based Real-Time Traffic Signal Timing Design Model Utilizing Smart Intersection Data
The smart intersection (SI) systems, as they are named in the Republic of Korea, are part of the ITS services implemented under local government projects with financial support from the central government. They collect real-time traffic data available at signalized intersections with advanced detect...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-07-01
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| Series: | Engineering Proceedings |
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| Online Access: | https://www.mdpi.com/2673-4591/36/1/32 |
| _version_ | 1797241218590048256 |
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| author | Sang-Tae Oh Jin-Tae Kim |
| author_facet | Sang-Tae Oh Jin-Tae Kim |
| author_sort | Sang-Tae Oh |
| collection | DOAJ |
| description | The smart intersection (SI) systems, as they are named in the Republic of Korea, are part of the ITS services implemented under local government projects with financial support from the central government. They collect real-time traffic data available at signalized intersections with advanced detection systems for surveillance purposes only. A traffic signal method utilizing such valuable data has been desirable but unavailable as yet in practice. This paper proposes a new approach to designing traffic signal timings, reflecting the demand changing in real time, by utilizing SI surveillance data. The proposed artificial neural network model generates suitable traffic signal timings trained to be near optimum based on surveillance data for each directional movement. |
| first_indexed | 2024-04-24T18:19:50Z |
| format | Article |
| id | doaj.art-10b7c41e071140d68208590ec7fb2cd8 |
| institution | Directory Open Access Journal |
| issn | 2673-4591 |
| language | English |
| last_indexed | 2024-04-24T18:19:50Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Engineering Proceedings |
| spelling | doaj.art-10b7c41e071140d68208590ec7fb2cd82024-03-27T13:36:30ZengMDPI AGEngineering Proceedings2673-45912023-07-013613210.3390/engproc2023036032A Study of Artificial Neural Network-Based Real-Time Traffic Signal Timing Design Model Utilizing Smart Intersection DataSang-Tae Oh0Jin-Tae Kim1Department of Transportation Policy and Systems Engineering, Korea National University of Transportation, 157 Cheoldobangmulkwan-ro, Uiwang-si 16106, Republic of KoreaDepartment of Transportation Policy and Systems Engineering, Korea National University of Transportation, 157 Cheoldobangmulkwan-ro, Uiwang-si 16106, Republic of KoreaThe smart intersection (SI) systems, as they are named in the Republic of Korea, are part of the ITS services implemented under local government projects with financial support from the central government. They collect real-time traffic data available at signalized intersections with advanced detection systems for surveillance purposes only. A traffic signal method utilizing such valuable data has been desirable but unavailable as yet in practice. This paper proposes a new approach to designing traffic signal timings, reflecting the demand changing in real time, by utilizing SI surveillance data. The proposed artificial neural network model generates suitable traffic signal timings trained to be near optimum based on surveillance data for each directional movement.https://www.mdpi.com/2673-4591/36/1/32traffic controlsignal timingsdeep learningartificial intelligencesimulationreal time |
| spellingShingle | Sang-Tae Oh Jin-Tae Kim A Study of Artificial Neural Network-Based Real-Time Traffic Signal Timing Design Model Utilizing Smart Intersection Data Engineering Proceedings traffic control signal timings deep learning artificial intelligence simulation real time |
| title | A Study of Artificial Neural Network-Based Real-Time Traffic Signal Timing Design Model Utilizing Smart Intersection Data |
| title_full | A Study of Artificial Neural Network-Based Real-Time Traffic Signal Timing Design Model Utilizing Smart Intersection Data |
| title_fullStr | A Study of Artificial Neural Network-Based Real-Time Traffic Signal Timing Design Model Utilizing Smart Intersection Data |
| title_full_unstemmed | A Study of Artificial Neural Network-Based Real-Time Traffic Signal Timing Design Model Utilizing Smart Intersection Data |
| title_short | A Study of Artificial Neural Network-Based Real-Time Traffic Signal Timing Design Model Utilizing Smart Intersection Data |
| title_sort | study of artificial neural network based real time traffic signal timing design model utilizing smart intersection data |
| topic | traffic control signal timings deep learning artificial intelligence simulation real time |
| url | https://www.mdpi.com/2673-4591/36/1/32 |
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