Fuzzy Graph Coloring for Traffic Signal Phase Optimization at Adjacent Urban Intersections

Authors

  • Sri Puspita Dewi I Yado Program Study of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Negeri Gorontalo, Gorontalo, Indonesia
  • Nurwan Program Study of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Negeri Gorontalo, Gorontalo, Indonesia
  • Djihad Wungguli Program Study of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Negeri Gorontalo, Gorontalo, Indonesia
  • Nisky Imansyah Yahya Program Study of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Negeri Gorontalo, Gorontalo, Indonesia
  • Armayani Arsal Program Study of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Negeri Gorontalo, Gorontalo, Indonesia

DOI:

https://doi.org/10.31851/sainmatika.v23i2.21601

Keywords:

Fuzzy graph, fuzzy graph coloring, chromatic number, traffic light optimization, adjacent intersections

Abstract

Traffic congestion at adjacent intersections is a critical urban mobility problem as vehicle queues and turning conflicts directly influence nearby performance. Conventional fixed-phase systems often fail to accommodate heterogeneous and fluctuating flows, especially when intersections are treated independently. This study aims to optimize traffic light phase arrangements at two adjacent intersections on Prof. Dr. Jhon Aryo Katili Road, Gorontalo, using a fuzzy graph coloring approach.Vehicle flow data were collected during morning and afternoon peak periods and converted into Passenger Car Equivalent (PCE) values. Each traffic movement was represented as a vertex, while conflicting movements were modeled as edges in a fuzzy graph. Triangular membership functions classified traffic intensity, followed by $\alpha$-cut-based fuzzy graph coloring to determine feasible signal phases.The results yield a chromatic number of eight, representing eight traffic light phases. This indicates that fuzzy graph coloring provides a more conflict-sensitive and adaptive structure than the existing three-phase system. The main contribution lies in extending fuzzy graph optimization from isolated to adjacent intersection settings, providing a mathematical basis for more efficient urban traffic management.

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Published

2026-07-22

Issue

Vol. 23 No. 2 (2026): Sainmatika : Jurnal Ilmiah Matematika dan Ilmu Pengetahuan Alam

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How to Cite

Fuzzy Graph Coloring for Traffic Signal Phase Optimization at Adjacent Urban Intersections. (2026). Sainmatika: Jurnal Ilmiah Matematika Dan Ilmu Pengetahuan Alam, 23(2), 100-116. https://doi.org/10.31851/sainmatika.v23i2.21601