Scenario Discovery for Resilient Urban Systems (or, The Future Is “Big Data”)
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2017-04-25
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TRIS Online Accession Number:01701450
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Edition:Year 25 Final Report
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Abstract:Our original primary aim was to formalize techniques for representing and propagating uncertainty in integrated land-use and transportation (LUT) models and demonstrate how this more rigorous characterization of uncertainty can lead to more robust and flexible systems, and improve decision-making. The project successfully completed the development, calibration and partial validation of an integrated land use-transport (LUT) model for the Boston metropolitan area and ran the model under alternative scenarios up to 2030. The LUT model was implemented in commercial software, using Citilabs’ Cube Voyager (four-step transport model) and Cube Land (land use model). Our original intention was to implement the models in a cloud-based computing environment, but the costs were too prohibitive. In the end, we used a machine with 20 dual core I7 chips (40 threads) which allowed parallelization of model processes. For the operational LUT model, we compiled a multi-source database on travel demand, transport supply, demographics, the housing market, employment, and land uses from 1970 to 2010 for the model area (Boston Metropolitan Area).
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