Determination of efficient green wave corridors in the transportation network with the community detection method

Öztemiz F., Karcı A.

JOURNAL OF POLYTECHNIC-POLITEKNIK DERGISI, cilt.27, ss.35-45, 2024 (ESCI) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 27
  • Basım Tarihi: 2024
  • Doi Numarası: 10.2339/politeknik.1074962
  • Dergi Adı: JOURNAL OF POLYTECHNIC-POLITEKNIK DERGISI
  • Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), TR DİZİN (ULAKBİM)
  • Sayfa Sayıları: ss.35-45
  • Anahtar Kelimeler: Green wave, community detection algorithms, walktrap algorithms, signaling systems, transportation network
  • İnönü Üniversitesi Adresli: Evet

Özet

Signaling systems play an important role in managing urban transport networks. Optimizing signaling systems significantly reduces traffic density in transport networks. One of the popular methods applied to increase the efficiency of the signaling system is the green wave application, which means the coordinated operation of the signaling systems. The green wave system prevents vehicles from being repeatedly caught in red light, reducing travel time, waiting time on the roads and carbon emissions of vehicles. The problem that will arise at this point is on which intersection points the green wave system will be applied. In this study, vehicle counting and signaling data of the city of Malatya were used and the transportation network data was converted into a weighted graph. By applying the walktrap community detection algorithm to the transportation network, the intersection points are grouped according to the vehicle transition similarities on them. It was applied to the green wave system physically for the intersection points in 2 different groups determined. The results show that there are significant increases in the number of vehicles passing per unit time in the regions where green waves are applied. This situation has resulted in a decrease in the number of vehicles waiting at red lights and significant reductions in carbon emissions from stationary vehicles into the atmosphere.