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The factors are applied to individual origin-destination pairs using a correspondence between MTC TAZs and Pleasanton model TAZs. Therefore, the Pleasanton model will include higher transit shares for trips to downtown San Francisco than for trips to Livermore from the same residential neighborhood. In addition, changes in future mode shares are included in the forecasts to the extent that the changes are included in the MTC model. This "adjustment" approach ensures that the City's demand tool employs consistent mode choice methodology as contained in the latest CCTA Model, without the City having to go to the expense of maintaining and operating a separate mode choice sub-model. Feedback Loops and Peak Hour Spreading A special feedback procedure was created to feed the congested travel times predicted at the end of the model run back to the trip distribution stage of the process. This procedure is most important for the distribution of work trips and has been incorporated into many of the Bay Area regional modeling efforts. In addition, unlike other traffic forecasting models in the region, the City of Pleasanton's traffic forecasting model is sensitive to the impacts of increased congestion on the temporal spreading of peak hour trips. As travel times increase for certain origin to destination trips, travelers are shifted to the "shoulders" and are not expected to begin or end their trip within the chosen peak hour. This effectively reduces the peak hour demand trip table to levels that can just be accommodated during the peak hour. This spreading process was equilibrated both for base and future years to estimate appropriate congested trip table forecasts. This peak spreading process ensures that the model will produce reasonable and realistic forecasts of peak hour traffic congestion (i.e., we do not see the extreme overloading of roadway facilities in the peak hour with demand far exceeding their capacity). Model Calibration and Validation Model calibration takes place at each step in the model process and involves initial specification and then refinement of the various parameters and coefficients by comparing model results to observed conditions. Model validation refers to comparing the model outputs (traffic volumes) to observed conditions (traffic counts, survey results, etc.). During validation, adjustments are primarily made to model inputs, such as the road network and base year land uses, rather than calibrated parameters such as trip generation rates or peak factors. Once validated, the model can be used to predict future travel patterns with a high degree of confidence. City of Pleasanton Travel Demand Forecasting and Micro-Simulation Models Page 11 January 23, 2007