In this study, max flow analysis processes are carried out with a graph theory-based approach that can be used in optimizing the traffic load in transportation networks. The data used in the study consists of 2 years of vehicle number data consisting of 438 million vehicle passes of a real city. Bottleneck points affecting traffic flow, maximum flow values, and effectiveness values of traffic generating and attracting locations were determined in the uniquely created transportation network. The Ford-Fulkerson algorithm was used to determine the maximum flow and bottleneck road connections in the designed transportation network. According to the maximum traffic flow to the junction point, the most effective junction points were determined by the PageRank algorithm. In addition, a unique algorithm is presented in the study that determines the effective intersection points that transfer vehicle traffic at maximum capacity to all junction points according to the maximum demand capacity data.
Primary Language | English |
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Subjects | Artificial Life and Complex Adaptive Systems, Artificial Intelligence (Other), Transportation and Traffic |
Journal Section | Araştırma Makalesi |
Authors | |
Early Pub Date | December 25, 2023 |
Publication Date | December 28, 2023 |
Submission Date | July 11, 2023 |
Acceptance Date | October 23, 2023 |
Published in Issue | Year 2023 Volume: 12 Issue: 4 |