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age. Activity- based models allow for a richer household composition and market segmentation. Static equilibrium assignments are important. After level of service E is reached, volume demand functions are questionable. This issue affects mode choice, air qual- ity analysis, activity location choice, and time- of- day choice. Volume- to- capacity ratios do not necessarily pin- point problems in a way that can be prioritized. The lack of vehicle dynamics, such as acceleration and stopping, makes analysis of air quality issues a problem. The general assumption of a static land use compo- nent negates the effect of infrastructure investments on housing and job location. It does not consider the effects of not building sufficient transportation infrastructure on land use. Static land use assumptions can either underestimate or overestimate needs. I would like to offer a few suggestions on the direction in which modeling should be moving. First, we need to move toward the use of tour- based or better activity- based models. Second, we need to continue to develop large- scale microsimulation or large- scale dynamic traffic assignment (DTA) models. Third, there is a need to deploy integrated land use models for major planning exercises. There are some limitations with the current tour- based models. The model structure is typically similar to the trip- based model structure, which begins with activ- ity location and mode. It is possible to improve on the trip- based approach, however, because the activity pat- tern is known at mode choice. With network microsim- ulation, it becomes evident that location choice for transit users and walk trips might be fundamentally dif- ferent than for automobile trips. There is a lot of activity focused on current microsim- ulation and DTA limitations. TRANSIMS provides an approach to addressing many concerns, including the need for more scale and more granularity. There are limitations with currently available land use models. Some of these limitations focus on competing technologies and tools that add complexity, as well as additional staff and financial resource needs. Land use modeling should be attempted, however, even if it is only a simple approach. A simple technique can begin the institutionalization of using land use models with techni- cal staff and policy makers. We need to continue to focus on bridging the gap between the use of trip- based models and the use of more advanced tour- based models. Tour- based models are in practice in a few places, but additional implementation is needed. There are still some improvement needs with tour- based models, but they produce better results than trip- based models. Minor improvements from common postprocessing are not enough with assignment. There is a need to explore other available methods. We have much to learn from the experiences with the use of dif- ferent models in different areas. DEVELOPING DETAILED PROJECTIONS OF IMPACTS OF SPATIAL SEPARATION, MITIGATION, SUPPLY AND DEMAND, INFRASTRUCTURE, AND STRATEGIES IN A VOLATILE ECONOMIC, SOCIAL, AND PHYSICAL ENVIRONMENT Edward Granzow My comments focus on software systems and their appli- cation in travel modeling. As we consider travel demand models, it is important to focus on the uses of these mod- els. This approach helps us to better understand what the various models can and cannot do, where we stand in terms of current and expected innovative practice, and challenges we still face. My comments focus on both operational and theoretical aspects of travel modeling. Any approach we take will have potential costs and benefits in terms of the operational environment and in terms of the theory. It is important to remember that we are moving from a modeling environment that is fairly flexible and easy to use, and that has benefits to MPOs in solving real- world problems, into an environment where there is a lot more fidelity. There are a number of items that are important to consider in moving toward more widespread applica- tion of advanced models. The innovations in travel models that we are dis- cussing are phenomenal, but more work is still needed before we will see widespread application. It is impor- tant to remember that advanced travel demand models are not a magic solution. There is still uncertainty related to the future demands that we may face as modelers and I do not think that we have a coherent strategy for addressing these demands. We need a broader perspective as we examine the future of travel demand modeling. The title of my presentation, Developing Detailed Projections of Impacts of Spatial Separation, Mitigation, Supply and Demand, Infrastruc- ture, and Strategies in a Volatile, Economic, Social, and Physical Environment, highlights some of these points. The first few words are the key part of the title. Most of the words after that are modifiers. As modelers, we are being asked to provide more information about the future. We are being asked to deal with a larger number of varied assumptions as model inputs. I use the concept of âfeasible regionsâ to potentially identify an area of a graph that represents the possible outcome of a situation given a number of model runs. Models are more com- plex today. This complexity may limit the viability of models to conduct âwhat ifâ analyses. Also, the cause and effect and impact chains become less clear. Model complexity can obscure practical applications. The three wordsâ spatial, separation, and mitigationâ relate to the way in which telecommunications is interact- ing with transportation. Telecommunications is changing 11MOVING INNOVATIVE MODELS INTO PRACTICE
