Researches transportation system sustainability including smart growth, alternative vehicle and fuel technologies, intelligent transportation systems, pricing incentives, green logistics, and alternative transportation modes.
This research area will link the ISTL to UB’s Energy Diversification Initiative through work on transportation energy issues (e.g. plug-in hybrid vehicles). The area is also extremely well aligned with one of the Power of SUNY2020 “Six Big Ideas,” namely “Energy-Smart New York.”
With worldwide concerns about energy shortage and global warming, finding methods to cut down on energy consumption and emissions from surface transportation has become of paramount importance. Different strategies are currently being studied for their potential to mitigate the negative impacts of the surface transportation sector on the environment. The focus of this study is on an Intelligent Transportation Systems (ITS) strategy which involves providing route guidance to travelers with the objective of minimizing emissions or fuel consumption, as opposed to the traditional objective of minimizing travel times. Specifically, this study conducts a realistic assessment, using a real-world case study, of the likely environmental benefits of environmentally-based route guidance.
Several features distinguish this study from previous reported research. First, the research utilizes a realistic case study of a medium-sized metropolitan area in the United States with a population of about 1.2 million. Second, the research applies the latest state-of-the-art models on both the transportation as well as the environmental modeling side, through the development of an integrated model combing the Transportation Analysis and Simulation System (TRANSIMS) model and the Multi-Scale MOtor Vehicle Emissions Simulator model (MOVES). Third, the integrated model is used to approximate “Green User Equilibrium”, and to investigate the impact of market penetration on the likely environmental benefits of green routing.
Finally, the findings suggest that reductions in emissions of sizeable magnitude are possible with green routing, but the savings in fuel consumption appears to be more modest.
In this project, recently awarded by New York State Energy Research and Development Authority (NYSERDA), Dr. Sadek and Dr. Wang will first identify the most appropriate methods that would allow for better reflecting the benefits of smart growth in travel demand forecasting practice. Using a case study from the Greater Buffalo/Niagara metropolitan area, the project will then demonstrate how these methods can be best implemented. Finally, the project will develop a decision support system (DSS) that would capitalize on the increased sensitivity of demand forecasting models in order to optimally design the land use so as to reduce VMT. With these tools, planners would be able to present a convincing case for smart growth, which should encourage more jurisdictions to adopt and implement such concepts.