Better planning tools are increasingly available to help MPOs understand the impact of their decisions on the transportation network and the natural and human environment. A number of decision support tools are available to communities to help them tackle land use, community development, economic development, and environmental protection challenges. Geographic Information Systems (GIS)-based decision support and visualization tools assist planners with conveying information to stakeholders to encourage successful community design and informed decisionmaking. Examples of planning tools include transportation models, land use models, GIS, GIS-based decision support tools, scenario planning models, and satellite imagery.
Models are simulations of the "real world" that can be used to show the impact of changes in a metropolitan area on the transportation system (such as adding a new road or transit line, or increases in population or employment). Travel models may be used to test the travel impacts of changes in land use, economic development, fuel and parking cost, and new highway or transit system capacity.
Three important ingredients are part of any model used for transportation analysis:
Key base, or current-year characteristics of travelers and the transportation system, described in terms of quantifiable variables (e.g., the number of highway travel lanes, transit service headways, household size and income, number of vehicles per household, employment patterns by type and job classification, etc.).
The relationship between these variables and the travel behavior of individuals (e.g., the more automobiles per household, the greater the number of automobile trips per household). This relationship is most often expressed in mathematical terms.
Future-year forecasts of key traveler and transportation system characteristics. This relationship is the same for all individuals and is constant over time.
Challenges to the validity of travel models often focus on one of these three assumptions.
For the past 40 years, transportation professionals have used a four-step approach in modeling transportation demand. Most modeling approaches use some form of these steps today. Once some understanding has been established as to what the land use, population, and employment levels are in a study area, the four modeling steps are:
Trip generation: Estimating the number of trips generated in a small geographic area, called a zone, or at a particular location, and attracted to another zone or particular location, based on the assumed relationship among socio-economic factors, land use characteristics, and the number of trips. Trip generation then leads to:
Trip distribution: Estimating the number of trips that originate in every zone in the study area, with destinations to every other zone. The result is a trip table that is used in:
Mode split: Estimating, for the number of trips predicted between each origin and destination, the number of trips made via each type of mode that is available for that trip. Thus, "x" percent are likely to drive alone, "y" percent are likely to take transit, "z" percent are likely to ride-share, etc. Mode split leads to:
Network assignment: Estimating the number of trips via a particular mode that will take specific paths through a road or transit network. The end result, when all trips are assigned to a network, is an estimate of the total number of trips that will use each link in the network. When compared to the capacity of this link, planners can forecast the level of congestion that will occur at that location. This becomes the basis for assessing the performance of the transportation system.
What are other types of models?
Four-step models are commonly used to predict the demand for transportation services. Transportation planners and engineers also use other types of models to analyze and evaluate the performance of transportation systems and resulting impacts.
Land use models are used to forecast future development patterns as well as the potential for proposed transportation improvement to "induce" new or accelerated land development in particular areas. The output of land use models typically provides the input to the trip generation step of the travel forecasting model.
Emissions models use the output of travel forecasting models—simulated highway travel as expressed by vehicle miles traveled—in projecting the tons of key pollutants emitted in the exhaust of vehicular trips. Estimates of the tons of emissions of hydrocarbons, nitrogen oxides, and particulates from emissions models provide important information for use in air quality analysis.
Several metropolitan areas, such as New York, San Francisco, and Columbus, Ohio have implemented advanced tour or activity-based models, which model travel differently from trip-based models. Tour-based models, for instance, keep track of travel activity throughout the day and can assemble multiple trip legs (chained trips) into tours. For example, a parent may leave work, pick up the children at day care, and stop at the grocery store on the way home. These separate trips would be linked together into a tour and, when taken as a whole, the modeled travel behavior of this parent would likely be different than if all of these trips were considered separately.
An activity- or tour-based model is able to show the extent to which mixed-use neighborhood residents tend to reduce their automobile use by taking transit, walking or bicycling, or accomplishing several activities in one automobile trip in cases where mixed-use development places retail, entertainment, and office locations close together. The modeling approach, more disaggregated in time, space, and activities, is also better suited to analyzing other complex policy alternatives such as variable pricing, flexible working hours, nonmotorized travel, and induced demand.
Results of a model are still only estimates—they cannot provide a definitive picture of what will happen in the future. Much like economic projections, transportation forecasts are greatly affected by the long-term economic health and attractiveness of the region, by population changes, and by the individual behavior of each person using the transportation system, which no one can predict.
Model results are only as good as the data that go into the model. MPOs must use the most current socioeconomic and census data available, especially if the region is growing rapidly. MPOs should make every effort to explain the information and assumptions that went into creating the model in plain, understandable terms. Finally, it is important that the models periodically be validated against observed conditions. And, the state, MPO, and transit operators should have a schedule for periodic re-survey of the usage and performance patterns of their systems (e.g. transit onboard and roadside origin/destination surveys).
Visualization techniques are methods used by states and MPOs to communicate information used in the development of transportation plans and programs to the public, elected and appointed officials, and other stakeholders in a clear and easily accessible format. This could involve use of one or more of a broad range of information dissemination tools, including maps, pictures, or displays, with the intention of promoting improved understanding about existing or proposed transportation plans, policies, and programs.
Visualization techniques can be used through the process, including in developing planning documents, on websites, and at public outreach and information sessions. Through visual imagery, the complex character of proposed transportation plans, policies and programs can be portrayed at appropriate scales and from different points of view, providing the public and decision makers with a clear idea of the proposals and likely impacts to the human and natural environment. In addition to their use in public involvement, visualization techniques are increasingly used as tools for improved decisionmaking for context-sensitive solutions.
A Geographic Information System (GIS) is a collection of computer software, hardware, and data used to store, manipulate, analyze, and present geographically referenced information. A GIS can be used both for analysis and as the basis for many of the visualization techniques described above. In transportation planning, GIS is typically used to compile and "overlay" multiple sets of data linked to particular geographic locations. Using GIS, transportation professionals can holistically and efficiently view multiple items of interest about a particular geographic area including transportation facilities, operations, demographics, environmental and cultural resources, public lands, and others. As an aid to environmental analysis, GISs also are used to overlay key features of the human and natural environment for the purpose of identifying corridors and subareas with the highest concentration of sensitive areas.
One use of models is in assessing the transportation impacts of alternative possible future policy scenarios. Scenario testing, also known as scenario planning, is an important policy analysis and public involvement tool for planners and involves undertaking long-range strategic planning studies testing alternative sets of future-year assumptions and engaging stakeholders and the public in reviewing the implications.
Instead of concentrating on one aspect of planning for the future, many tools used in scenario planning estimate the impacts of people's decisions today on the land use, transportation system, and environment of tomorrow. Additionally, these tools take into account the interconnections between these three aspects of planning. For example, if a change to the transportation system is proposed for an area, models can estimate its land use and environmental impacts. Powerful tools provide for more comprehensive geographic analysis and visualization using interactive analysis tools and a decisionmaking framework. Scenario planning tools can be used to view, analyze, and understand land-use alternatives and their impacts for informed decisionmaking.
Cambridge Systematics and Transmode Consultants, Multimodal Corridor and Capacity Analysis Manual: National Cooperative Highway Research Program Report 399. Transportation Research Board, 1998.
For the FHWA's Travel Model Improvement Program (TMIP) see http://tmip.fhwa.dot.gov/
See also Meyer, M. and E. Miller, Urban Transportation Planning: A Decision-Oriented Approach. New York: McGraw Hill, 2001.
For NETC 00-6: Effective Visualization Techniques for The Public Presentation Of Transportation Projects see www.netc.uconn.edu/pdf/netcr48_00-6.pdf
For more on TRB's work on visualization in transportation see http://www.trbvis.org/
For AASHTO's Visualization in Transportation: A Guide for Transportation Agencies see http://tmip.fhwa.dot.gov/
For TRB's Visualization Symposium Proceedings see www.teachamerica.com/viz/viz2006.html
For NCHRP's Visualization for Project Development see http://pubsindex.trb.org/document/view/default.asp?lbid=792999
For FHWA's Executive web-based Geographic Information System see http://hepgis.fhwa.dot.gov/hepgis_v2/Welcome.aspx
For FHWA's Frequently Asked Questions Applying 2000 Census Data to Urbanized and Urban Areas see: http://www.fhwa.dot.gov/planning/census/faqa2cdt.htm