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<br />ATTACHMENT 2 <br /> <br />The City of Pleasanton <br /> <br />Travel Demand Forecasting and Micro-Simulation Models <br /> <br />Introduction <br /> <br />A new City traffic modeling process was developed for the Year 2001 Baseline <br />Report to more accurately reflect peak hour traffic conditions in and through the <br />City. The goal was to achieve more realism in the traffic projections used by the <br />City for determining the impacts of new development and assessing the need for <br />street improvement projects. The tools in this modeling process were further <br />refined in 2003 and then again in 2006 with regard to school, commuter and cut- <br />through trips. The land use estimates, traffic generation rates, and signal time <br />assumptions were also updated in 2006 using the most current information <br />available. <br /> <br />The City of Pleasanton's traffic modeling process combines the power of a City- <br />specific travel demand model (CubeNoyager) with an intersection operations model <br />(Synchro/SimTraffic). <br /> <br />The travel demand model is designed to test: <br /> <br />. Land use alternatives, including potential updates ofthe General Plan <br />. Roadway network alternatives, including street widenings and extensions <br />. Impacts of proposed land use developments <br /> <br />The Synchro/SimTraffic micro-simulation tool is designed to test: <br /> <br />. Signal timing/coordination improvements <br />. Lane additions at and between intersections <br />. Left and right turn pocket extensions <br />. Freeway ramp metering and interchange improvement options <br /> <br />Travel Demand Model <br /> <br />The City of Pleasanton's travel model is intended to provide reliable traffic forecasts <br />to support the City in transportation and land use studies, including potential <br />updates of the General Plan. Therefore, the model must be responsive to local land <br />use changes. It must be able to generate results at a detailed level including <br />specific intersections. Because traffic patterns in Pleasanton are strongly affected <br />by congestion on regional routes, the model must account for these congestion <br />effects. <br /> <br />City of Pleasanton <br />Travel Demand Forecasting and Micro-Simulation Models <br /> <br />Page 1 <br />January 23, 2007 <br />