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31 Those freight components that use commodities have results if a conflict arises. As a condition for Wisconsin many commodity categories. Vermont has the fewest cat- gaining the MPOs' cooperation in building its model, the egories at 6 and Ohio has the largest number of categories state needed to ensure their two largest MPOs that the at 32. There is a cluster of four states (Kentucky, Michi- statewide model would not be used for urban forecasts. gan, Virginia and Wisconsin) using between 25 and 28 Except for Rhode Island, where an MPO model is available, categories. statewide models are not used directly for urban forecasts. Integration efforts thus far have been heavily influenced by the need to share data and to provide external station fore- LAND USE AND ECONOMIC ACTIVITY casts for MPO models. A number of states formally consider economic activity as ei- ther an input to their forecasts or as a post-processor of model outputs. Ohio's new model and Oregon's model have land VALIDATION use and economic activity calculations that are tightly inter- All statewide models have been validated or are undergoing woven with the rest of their components. Chapter three in- validation. The following is a list of the types of data used cludes a discussion of Ohio's model. Indiana and Maine during validation. specifically mentioned using a commercial regional eco- nomic forecasting model. Montana's HEAT is an economic Passenger vehicle counts model with a freight component. A few other states indicated (24) that they are considering using a regional economic fore- Truck counts (15) casting model to post-process the results of their statewide Comparisons to national default trip generation travel forecasts. values (11) Commuting OD flows from STATEWIDE AND URBAN MODEL INTEGRATION CTPP (11) Comparisons to average values (or other statistics) Good linkages between statewide and urban models are de- from own travel surveys (8) sirable, but not necessary. Rhode Island is a special case, be- Known trip length frequency distribution(s) cause its statewide model is an MPO model; therefore, there (8) is no need to integrate. Here are some integration activities Comparisons to average values from similar and the number of states participating in each. states or cities (7) MPO models (5) Statewide model provides independent estimates Counts of passengers on buses (3) of traffic in areas covered by urban Counts of passengers on trains (3) models (13) MPO OD studies (2) Statewide model is used to develop external Goods production by sector or zone (1) station forecasts for the urban Data from cordon surveys (1) models (13) HPMS VMT estimates (1) Statewide and urban models share geographic systems such as zones or networks (10) States tended to use a variety of data sources for valida- Statewide and MPO models use similar computational tion. All states already involved in validating their models steps, trip purposes, base-year, or modes to promote used passenger car volumes. Most states also used truck compatibility (7) counts. Statewide model shares GIS databases with MPO models (6) Criteria for validation of statewide models closely follow Urban models incorporated as part of the statewide those found in urban models. Each state chose to use a variety model (6) of measures. Institutional issues regarding the statewide model provide forecasts that might conflict with VMT by functional class absolute MPO models (3) deviation (18) Statewide model provides impedances for use Link root mean-square error (RMSE) by volume in the MPO models (1) strata (17) Screenline count absolute Most statewide models are coarser than MPO models deviation (17) within urban areas; therefore, the relative validity of the Link absolute deviation (12) statewide versus urban models is obvious. Seven states Cordon count absolute deviation (10) commented that although their statewide model can pro- Correlation coefficient between link volume duce forecasts for urban areas, they defer to MPO model forecasts and counts (8)