This paper presents an augmented network model to represent urban transit system.Through such network model,the urban transit assignment problem can be easily modeled like a generalized traffic network.Simultaneously,...This paper presents an augmented network model to represent urban transit system.Through such network model,the urban transit assignment problem can be easily modeled like a generalized traffic network.Simultaneously,the feasible route in such augmented transit network is then defined in accordance with the passengers＇ behaviors.The passengers＇ travel costs including walking time,waiting time,in-vehicle time and transfer time are formulated while the congestions at stations and the congestions in transit vehicles are all taken into account.On the base of these,an equilibrium model for urban transit assignment problem is presented and an improved shortest path method based algorithm is also proposed to solve it.Finally,a numerical example is provided to illustrate our approach.展开更多
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, su...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.展开更多
基金supported by the National Natural Science Foundation of China (71071016,70901005)the Fundamental Research Funds for the Central Universities (2009JBM040,2009JBZ012)the Foundation of State Key Laboratory of Rail Traffic Control and Safety (RCS2010ZT001)
文摘This paper presents an augmented network model to represent urban transit system.Through such network model,the urban transit assignment problem can be easily modeled like a generalized traffic network.Simultaneously,the feasible route in such augmented transit network is then defined in accordance with the passengers＇ behaviors.The passengers＇ travel costs including walking time,waiting time,in-vehicle time and transfer time are formulated while the congestions at stations and the congestions in transit vehicles are all taken into account.On the base of these,an equilibrium model for urban transit assignment problem is presented and an improved shortest path method based algorithm is also proposed to solve it.Finally,a numerical example is provided to illustrate our approach.
基金supported by National Natural Science Foundation of China under Grant Nos.71071016,71131001National Basic Research Program of China under Grant No.2012CB725400supported by Fundamental Research Funds for the Central Universities under Grant Nos.2012JBM056,2012JBZ005
文摘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.
