摘要: |
Vehicle-generated emissions remain a serious threat to the health of urban and suburban communities. Among the strategies implemented to address this environmental problem are area- and cordon-based pricing (ACP) schemes. Experiences in major cities such as London, Stockholm, and Milan show that ACP schemes are effective in reducing traffic emissions and the related public health risks. However, designing ACP schemes continues to be a challenging task given the complexities of estimating the effects of this type of strategy. In response to this design problem, optimization-based approaches have been proposed to aid transportation planning agencies in determining optimal charging boundary locations and toll levels. Existing engineering methodologies focus only on congestion-related goals, as well as employing an aggregate representation of travel demand corresponding to a single design period (e.g., the morning peak hour). The existing models, however, do not account for the impacts of ACP schemes on pollutant distribution throughout the day, nor the resulting effects the levels of pollutant exposure experience by the public. In this project an ACP design approach is proposed that considers: a) the effects on pollutant concentrations of the pricing scheme, b) the effects on travelers’ activity, schedule, and time-use preferences at a disaggregate level, c) the space-time distribution of pollutants along with the space-time distribution of travelers, and d) planning goals related to system-wide congestion levels and public health. Two types of planning problems are considered. In the first problem, it is assumed that the decisionmaker is interested in designing a pricing schemes that achieves a mobility-related goal, while simultaneously reducing pollutant concentration levels below a preestablished threshold. The second problem adds an environmentally-oriented objective to the decision-makers plans. For the purpose of simulating the human exposure of pollutants at the level of individual agents, a new activity-based travel model is presented. The proposed ACP design problems are formulated as bi-level, simulation-based optimization problems. A problem’s upper-level is composed of the policy makers’ goals, which guide the selection of charging boundary’s location and its associated tolling levels. The travelers’ response to the policy maker’s decisions, as well as the resulting system-wide impacts, are analyzed in the lower-level. The lower-level model system is composed of five sub-models: (a) models to simulate the travel behavior changes caused by the pricing scheme, (b) a traffic assignment model to estimate the distribution of traffic in the network, (c) a traffic emissions model, (d) a pollutant dispersion model, and (e) a pollutant exposure model. To solve the proposed design problems, two surrogate-based solution heuristics are proposed. A series of numerical tests are presented to illustrate the application and performance of the proposed methodology. |