Dr. Daniel Rodriguez-Roman, Assistant Professor of Civil Engineering at University of Puerto Rico, Mayagüez, presented a seminar during his visit to NYU Tandon this summer. His research focuses on transportation network design problems, evolutionary and surrogate-based optimization, and, recently, paratransit demand modeling and operations. He obtained his M.S. in Transportation Engineering from the University of California at Berkeley, and his Ph.D. in Transportation Systems Engineering from the University of California at Irvine.
Surrogate-Based Optimization Approach for the Design of Area Charging Schemes under Environmental Considerations
Abstract
Vehicle-generated emissions remain a serious threat to the health of urban and suburban communities. Among the strategies proposed to address this 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, the design of ACP schemes continues to be a challenging task, in part because of the complexities of estimating the effects of ACP 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 optimization methodologies, however, focus only on congestion-related goals and simulate travel demand using single-period aggregate models, without considering the impacts of ACP schemes on pollutant distribution throughout the day and its possible effects on the population.
In this presentation, Dr. Rodriguez-Roman discussed an ACP design approach that considers the effects of ACP schemes on: a) pollutant concentrations, b) travelers’ activity, schedule, and time-use preferences at a disaggregate level, and c) population exposure to vehicle-generated pollutants. Planning models are presented that capture societal 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 decision-maker is interested in designing a pricing schemes that achieves a mobility-related objective, while simultaneously reducing pollutant concentration levels below a pre-established threshold. The second problem adds an environmentally-oriented objective to the decision-makers plans. To solve the proposed design problems, two surrogate-based solution heuristics were presented. A series of numerical tests were discussed to illustrate the application and performance of the proposed methodology.
