DOAJ Open Access 2023

A Study of Artificial Neural Network-Based Real-Time Traffic Signal Timing Design Model Utilizing Smart Intersection Data

Sang-Tae Oh Jin-Tae Kim

Abstrak

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.

Topik & Kata Kunci

Engineering machinery, tools, and implements

Penulis (2)

Sang-Tae Oh

Jin-Tae Kim

Format Sitasi

APA MLA BibTeX

Oh, S., Kim, J. (2023). A Study of Artificial Neural Network-Based Real-Time Traffic Signal Timing Design Model Utilizing Smart Intersection Data. https://doi.org/10.3390/engproc2023036032

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Informasi Jurnal

Tahun Terbit: 2023
Sumber Database: DOAJ
DOI: 10.3390/engproc2023036032
Akses: Open Access ✓