Modeling the congestion cost and vehicle emission within multimodal traffic network under the condition of equilibrium

Traditional system optimization models for traffic network focus on the treatment of congestion, which usually have an objective of minimizing the total travel time. However, the negative externality of congestion, such as environment pollution, is neglected in most cases. Such models fall short in taking Greenhouse Gas (GHG) emissions and its impact on climate change into consideration. In this paper, a social-cost based system optimization (SO) model is proposed for the multimodal traffic network considering both traffic congestion and corresponding vehicle emission. Firstly, a variation inequality model is developed to formulate the equilibrium problem for such network based on the analysis of travelers’ combined choices. Secondly, the computational models of traffic congestion and vehicle emission of whole multimodal network are proposed based on the equilibrium link-flows and the corresponding travel times. A bi-level programming model, in which the social-cost based SO model is treated as the upper-level problem and the combined equilibrium model is processed as the lower-level problem, is then presented with its solution algorithm. Finally, the proposed models are illustrated through a simple numerical example. The study results confirm and support the idea of giving the priority to the development of urban public transport, which is an effective way to achieve a sustainable urban transportation.