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Much of the following network related excerpts are directly from Special Report 288, Metropolitan Travel Forecasting, Current Practice and Future Direction, Transportation Research Board, 2007.
Highway and transit networks are a principal means by which the supply side of transportation is represented. Networks are often represented in travel forecasting models using hierarchial relationships especially for the highway or roadway system. A typical highway network will include links ranging from high speed, high capacity (e.g., freeways) to low-speed, low capacity (e.g., residential streets). For transit, links will include fixed-guideway (e.g., passenger rail) to bus lines that operate in mixed-traffic on the roadway links. Non-auto modes such as walking, bicycling, or low-energy vehicles (e.g., neighborhood electric vehicles) are not usually represented in travel forecasting models. Hence, the networks for these modes are not included. The main reason for this exclusion is that most models were developed to address macro-level questions about the location or size of the roadway and transit network links (i.e., are new roads needed or what existing roads need to be widened).
While all models are representations of the 'real world', it should be noted that network models can be both very precise and accurate. The following quote from Toll Road Traffic & Revenue Forecasts, An Interpreter's Guide, Robert Bain, 2009 puts this in perspective especially as it relates to the differences between the supply and demand side of models.
"Traffic modeling is frequently described as being part science, part art. Modelling the base year supply-side -- the representation of the highway network today -- is the science part. It is frequently modelled with, literally, military precision using mapping data from GPS satelittes. This level of precision does not extend to the representation of the demand-side of the travel economy..."
Using geographic information systems (GIS), networks can be created that are built off survey and satelitte mapping data that is accurate to within a few inches. This level of accuracy and precision; however, should be considered in the context of the demand model and what happens when demand and supply are brought together in trip distribution and trip assignment.
The highway network is represented as individual, connected links between intersections. Usually all freeways, expressways, principal arterials, minor arterials, and feeder/collector routes are included. Data on roadway characteristics are associated with each link. Current highway networks range in size from 4,200 links for small MPOs to more than 20,000 for large MPOs.
The transit network (if there is one) is represented as routes for the various transit systems in the metropolitan area. Some of these routes run on the highway network and share highway links, while others are on their own right-of-way. Transit networks are typically more complex than highway networks because of the multiple modes involved and the need to consider operating frequencies and schedules. The vast majority of MPOs that have rail transit within their area include the entire rail network in their transit model. More than 80 percent of all MPOs and 90 percent of large MPOs include at least 75 percent of available express bus miles in their transit network. All of the large MPOs that reported having local bus service include at least three quarters of the local routes in their network. In contrast, more than 60 percent of the small MPOs and 20 percent of the medium MPOs that reported having local bus service include less than three-quarters of local service miles in their network.
The networks are connected to the traffic analysis zones (TAZs) using “centroid connectors,” which attach to the centroid at or near the center of each zone. Most networks are mapped and edited by using GIS software.
The four-step (or, in some cases, three-step) trip-based modeling process used by the vast majority of metropolitan planning organizations (MPOs) has evolved over a period of about 50 years. Originally conceived as an aid to developing transportation networks for large cites, the process was widely adopted to support planning for the urban segments of the Interstate highway system and to support the metropolitan planning requirements of the Federal-Aid Highway Act of 1962. Over the years, the procedures employed have been modified to address other planning questions and issues (e.g., air quality, transportation operations, Transit New Starts). While many projects have been planned and justified on the basis of data produced from models of this type, it has long been recognized that the process has many shortcomings.
Most network data is available/obtainable through direct field observations, aerial photography, or data resources such as those listed in the literature section of this site.
The visualization of networks typically occurs through mapping specific variables or attributes. These attributes can be displayed statically or dynamically and can take 2-D or 3-D forms.
Most travel forecasting or GIS software programs contain tools to conduct a variety of error or reasonableness checks related to the accuracy and connectivity of the network.
Travel demand is influenced by the network that is supplied. This relationship needs to be better understood so that induced and suppressed travel effects can be directly modeled by feedback to trip generation and long-range land use forecasts. The presence and completeness of bicycle, pedestrian, and low-energy vehicle/neighborhood electric vehicle networks on travel demand needs to better understood to justify future investments in these modes.