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20 Massachusetts and Ohio each had trouble obtaining employ- COMPUTER HARDWARE AND SOFTWARE ment data from another state agency. A few states reported Questionnaire Results funding shortfalls until the need for the model could be con- vincingly demonstrated. Wisconsin found trouble getting good All states reported using a high-speed personal computer to cooperation from the state's two largest MPOs and needed to run their existing models; typically running a version of the deal with a change in governor, who required time to under- Windows operating system. No other hardware requirements stand issues related to the statewide transportation plan. were noted. Overcoming Resistance A large majority of statewide models are built on software platforms originally designed for UTP. Oregon has constructed Literature on innovation often makes reference to the need its own software specifically for statewide modeling. Most for a "champion" to effect change. states use a GIS with their models; either a stand-alone GIS I've learned that in every state where models are maintained and package or one built into their UTP software. Computation actively used in the planning process that there is an evangelist and times vary considerably, ranging from only 30 s in South Car- visionary that drives the program. This person, by force of person- olina to 12 h in Maine. The median computation time is some- ality or position, is the key driver behind the success of the model. If this person retires or moves on to other things the modeling pro- where between 1 and 2 h; therefore, it is possible to conclude gram often dies. Thus, maintenance of the model is often more a that the computational burden is not large. reflection of the priorities and capabilities of the evangelist more than a systematic or carefully considered process (R. Donnelly, Statewide Travel Demand Models Peer Exchange, 2004). Example of the Use of Geographic Information Systems Cooperation is critical to an effective statewide travel In Louisiana, the statewide model network was developed based modeling process. on several existing DOT legacy databases including: It is important to build and maintain relationships between tech- nical staff and management. Well-established relationships be- Louisiana Road GIS file in Geomedia format; tween modeling staff and senior management make management Surface Type log file, a Microsoft Access database containing more willing to take a chance on a process that does not support mile post and key roadway attributes; and their initial preconceived ideas. Interest and support of model- Highway Needs Inventory Summary log file, another Mi- ing from `outsiders' is helpful. Those who used the modeling crosoft Access database, containing mile post and additional tools in the past support and advocate for its use on new projects. roadway attributes, roadway conditions, and future needs It is helpful to have advocacy from others external to the process information. that are perceived as nonbiased and those that may better under- stand non-traditional model outputs (W. Upton, Statewide Substantial resources were devoted by the model development Travel Demand Models Peer Exchange, 2004). consultant Wilbur Smith Associates (WSA) to make sure these files were rendered suitable for modeling purposes and were lin- ear referenced, facilitating future network update activities. Model Failure WSA first converted the original Geomedia Road GIS file to A number of statewide models have gone dormant. One ArcInfo, created a Route System, and used the dynamic seg- model developer writes: mentation method to link the Surface Type log and Needs In- ventory file to the GIS file. This process allowed WSA to access all the necessary network attributes from the two Microsoft Ac- Models fail for one of several reasons: cess databases. WSA decided to retain all of the links, including some local roads in the original GIS file for the Micro Model Vague or poorly defined goals and objectives. network. Developed with single purpose in mind. The Road GIS file was designed for the Louisiana Department Higher than expected maintenance and application costs. This in- of Transportation and Development (LADOTD) for nonmod- cludes the need for more highly skilled staff, the magnitude of eling functions and therefore was not suitable for modeling. data required (both in scale and scope), and inter-agency friction. The original GIS file did not represent a modeling network of Lack of management support (read: the models do not provide links and intersections. Network editing to split links was nec- information useful to decision makers in the metrics and time essary to represent intersections properly. Because some of frames they need). these intersections could be overpasses or underpasses, each The models are cumbersome and inaccurate. The models are required review so that network connections would replicate no better than the quality and quantity of the data used to de- ground conditions. velop them. Poor models are the only possible outcome from Many stub links were found in the original GIS file. Network building them with poor or scarce data. connectivity checks and editing were performed to make sure Failure to build linkages to economic models. Most state leg- the network was suitable for modeling. islatures tend to look at transportation problems as economic Additional roads were added, particularly within MPO areas. problems. Models that simply address traffic flows do not pro- The sources for the additions were from the MPOs' modeling vide the information on key linkages (and benefits) between network file or Census Topologically Integrated Geographic En- the economy and transportation. In some instances I've seen coding and Referencing (TIGER) line files. Toll roads, bridges, state legislators discount modeled outcomes because they are and automobile ferry links were identified and added to the Mi- at odds with, insensitive to, or seem uninformed by economic cro network, because they were not present in the state database. and market trends (R. Donnelly, Statewide Travel Demand With substantial manual editing and link additions, the existing Models Peer Exchange, 2004). GIS file mile post information was either missing or distorted.