Green Wave Control Model Simultaneously Considering Passenger Cars and Buses in Closed Road Networks

Existing green wave control methods for passenger cars and buses mainly focus on maximizing bandwidths at the arterial level. There is little research on green wave control for both at the closed road network level, which makes it difficult to improve the efficiency of the entire area. To address th...

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Veröffentlicht in:Applied sciences 2024-07, Vol.14 (13), p.5772
Hauptverfasser: Jing, Binbin, Huang, Zhengjie
Format: Artikel
Sprache:eng
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Zusammenfassung:Existing green wave control methods for passenger cars and buses mainly focus on maximizing bandwidths at the arterial level. There is little research on green wave control for both at the closed road network level, which makes it difficult to improve the efficiency of the entire area. To address this, a green wave control model that considers both passenger cars and buses in closed road networks is presented in this paper. The objective function of the model is to maximize the sum of the weighted bandwidths of passenger cars and buses on each segment of the road network. The relationships between car green bands, bus green bands, offsets, phase sequences, red time, green time, etc. are analyzed on the level of arterials and road networks, respectively, using time–space diagrams. Based on these analyses, the key constraints of the model are constructed accordingly. In addition, 0/1 variables and a sufficiently large positive number M are introduced to relax some of the constraints to ensure that the presented model has feasible solutions. The results of the numerical example demonstrate that compared with the fixed phase sequence schemes 1, 2, and 3, the total weighted bandwidth generated by the presented model increased by 9.5%, 16.4%, and 17%, respectively. Compared with the model without constraint relaxation, the presented model can still find a global, optimal solution when the common cycle time is fixed, while the model without constraint relaxation has no feasible solution.
ISSN:2076-3417
2076-3417
DOI:10.3390/app14135772