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.
Maximum Flow Ford-Fulkerson Algorithm Maximum Road Capacity Transport Network Graph Theory
Birincil Dil | İngilizce |
---|---|
Konular | Yapay Yaşam ve Karmaşık Uyarlanabilir Sistemler, Yapay Zeka (Diğer), Ulaşım ve Trafik |
Bölüm | Araştırma Makalesi |
Yazarlar | |
Erken Görünüm Tarihi | 25 Aralık 2023 |
Yayımlanma Tarihi | 28 Aralık 2023 |
Gönderilme Tarihi | 11 Temmuz 2023 |
Kabul Tarihi | 23 Ekim 2023 |
Yayımlandığı Sayı | Yıl 2023 |