Abstract
Congestion pricing strategy has been recognized as an effective countermeasure in the practical field of urban traffic congestion mitigation. In this paper, a bi-level programming model considering carbon dioxide emission is proposed to mitigate traffic congestion and reduce carbon dioxide emissions. The objective function of the upper level model is to minimize the sum of travel costs and the carbon dioxide emissions costs. The lower level is a multi-modal transportation network equilibrium model. To solve the model, the method of successive averages (MSA) and the shuffled frog leaping algorithm (SFLA) are introduced. The proposed method and algorithm are tested through the numerical example. The results show that the proposed congestion pricing strategy can mitigate traffic congestion and reduce carbon emissions effectively.
Highlights
Urban road traffic congestion has been one of the worldwide urban problems, which brings about many negative impacts
Scheme 1 does not implement traffic congestion pricing; Scheme 2 only considers the congestion into the objective function; Scheme 3 considers both the congestion and carbon emissions costs into the objective function
The results shows that the scheme proposed in this papper can mitigate traffic congestion and reduce carbon emissions more effectively than the other two schemes
Summary
Urban road traffic congestion has been one of the worldwide urban problems Some scholars proposed the optimal system (Verhoef [12], Yang and Zhang [13]) These papers regarded parts of the roads or links as tolled objects, and few guaranteed that the total carbon emissions would decrease after implementing the congestion pricing strategy. The corrected average speed model [16] is introduced to calculate the total carbon dioxide emission. Is introduced to calculate the total carbon dioxide emission, which is easier than micro-scale models It has good generalization and can apply a wide range of practical problems. The result shows that the traffic congestion pricing strategy will improve the efficiency of both public and private transport, while at the same time it is able reduce carbon emissions.
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