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The problem of traffic congestion and the environmental issues related to air pollution are among the essential problems of urban management that metropolitan cities are trying to mitigate. Given that the contribution of motor vehicles to air pollution is significant, both goals are achieved by managing urban transport. Among the various methods of travel demand management, congestion pricing is a very efficient measure. In this study, it is tried to simultaneously increase the efficiency of the transportation network and reduce the environmental effects by using a bi-level model for the multi-modal network. For this purpose, the upper-level model includes minimization of the objective function, i.e., pollution emission costs, and overall commuting cost. The lower level also has a transportation network model that provides the condition of user equilibrium. Two pricing schemes, including cordon-based and link-based pricing, are used to investigate and assist policymakers. The genetic and Frank-Wolfe algorithms have been used to solve the bi-level programming model. The proposed algorithm is also applied for a real network in Isfahan-Iran. The results of the proposed model for different pricing strategies were compared. According to the results, both pricing schemes mitigate traffic congestion and pollution, and the demand was shifted from the private car mode to public transportation. However, link-based pricing provides better performance than cordon-based pricing. According to the results, if there are conditions of link-based pricing, this scheme can reduce pollution and increase tolls revenue.JEL Classification: R41, O18, R48, C61, C63, Q53 |
