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Tri-Valley Transportation Council │ 2020 Nexus Fee Update Study <br />August 2021 │ Final 4 <br /> <br />2 FORECAST OF NEW DEVELOPMENT AND TRAVEL DEMAND <br />This chapter describes the methodology, assumption, and results for travel demand forecasting. <br />2.1 METHODOLOGY AND APPROACH <br />Travel demand forecasting was conducted using the current version of Contra Costa Transportation <br />Authority Travel Demand Model (CCTA TDM). The use of the CCTA TDM is consistent with the previous <br />2008 Nexus Study. Based on the outcome of initial discussions with the TAC, the following steps were <br />taken regarding the development of travel demand forecasts: <br />• Travel demand forecasting was reaffirmed to be based on the latest version of CCTA TDM. In 2019, <br />the CCTA TDM was updated to incorporate assumptions consistent with the current (as of 2017) <br />Metropolitan Transportation Commission (MTC) Regional Transportation Plan (RTP). A 2018 base <br />year validation was also completed as part of that update. The growth projections were based on <br />a base year of 2020 and a horizon year of 2040. Note that the CCTA TDM base year was updated <br />to reflect 2020 conditions and that the 2040 horizon year was also modified to address the specific <br />needs of this study. <br />• Land use assumptions for households and employment were broken down for the 2020 base and <br />2040 horizon years by jurisdiction and were distributed to member agencies for review. Detailed <br />data submitted to each jurisdiction included household and employment data at the traffic analysis <br />zone (TAZ) level. In addition, supplemental data from the Alameda County Transportation <br />Commission (ACTC) travel demand model was also provided to member agencies within Alameda <br />County. Kimley Horn worked closely with the individual agencies to appropriately finalize growth <br />forecasts prior to their use in the final modeling for this study. <br />Given that a recent land use forecast for the Tri-Valley region already exists as incorporated into the 2019 <br />update of the CCTA Model, it is important to provide a context for the basis of this forecast. Specifically, the <br />focus of this effort, unlike the more recent application of the CCTA model which was in support of a Region‐ <br />Wide RTP, is confined to a limited area that primarily includes City of Dublin, Pleasanton, Livermore, <br />Danville, and San Ramon and parts of unincorporated Contra Costa and Alameda counties. As this <br />constitutes sub‐area analysis (although the entirety of the model will be used during analysis), the typical <br />best practice includes carefully assessing land use within the study area to make sure that it is prepared in <br />a manner consistent with the specific goals of the study for which the TDM will be applied. It is important to <br />note that TDMs used in support of RTPs are prepared in accordance with strict control totals and, as such, <br />their land use forecasts do not necessarily reflect certainty as to whether a given development will occur, <br />rather they are more akin to a process of prioritization (the forecaster determines the magnitude and <br />location of development that is most likely to occur rather than determining whether something will NOT <br />occur). Not surprisingly, local jurisdictions sometimes have more detailed perspectives on whether certain <br />concentrations of development within their communities will occur before the RTP planning horizon. A land <br />use assessment, such as that carried out as part of a typical sub‐area analysis, is often an opportunity to <br />reconsider jurisdictional land use input without the necessary limitations that an RTP puts on land use <br />forecasting. <br />Based on these considerations and information shared by the TAC members, as well as input from staff <br />from the member agencies at several individual agency meetings, it was determined that the 2040 land use <br />forecast for the study area as included in the 2019 version of the CCTA TDM had unlikely development <br />patterns in several locations within the study area as compared to the collective perspectives of member