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pedestrians, and some who might have chosen to walk or ride a bicycle before the increase in traffic may no longer be willing to do so. · Street widening can create barriers. Several aspects of road design can affect the quality of nonmotorized transportation choices. Widening road facilities may be a boon to motorists, but for bicyclists and pedestrians (especially for those with disabilities), wider roads can be difficult and dangerous to traverse. · Transportation projects can displace or disrupt facilities. Bicycle trails, sidewalks, and transit stops may have to be moved to make way for other facilities. If so, it is likely that the nonmotorized facilities will be less accessible to at least part of the neighboring community. Even though relocating facilities to areas accessible to more people in total may be a wise thing to do, it can create accessibility problems for people who purposefully chose to live near the original location of the facility. STATE OF THE PRACTICE--ACCESSIBILITY Travel demand modeling is the primary tool for assessing the ability of people living within a particular area of a community to travel to desired destinations. This mode of analysis has been dominated over the years by trip-based models that use a four-step procedure for analysis consisting of (1) trip generation, (2) trip distribution, (3) mode split, and (4) traffic assignment. These models often do a good job of replicating aggregate travel patterns. However, they are limited in their ability to account for the attitudes, values, and constraints that determine travel patterns by the general population, much less specific groups such as minorities or those with low incomes. Activity-based approaches attempt to take into account the interdependences in trip decisions made by groups of individuals. These approaches generally are flexible enough to consider the way household members allocate and share resources and tasks among themselves, and jointly share activities that are dispersed in time and space. In other words, activity-based approaches can be more realistic for the purposes of analyses related to environmental justice (see RDC, Inc. 1995). Nevertheless, four-step travel demand modeling is a very useful tool for gauging road system performance--an essential part of assessing transportation user effects. Thus trip-based models can serve an important role in providing a preliminary analysis of the likely impact a proposed transportation change would have on accessibility by low-income populations and minority populations. Trip-based models The trip-based approach is founded on several assumptions: · The number of trips generated by a household is a function of household size (number of members) and the number of vehicles available. 169
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· Individuals always make optimal decisions with respect to their travel arrangements; in other words, an individual can identify and pursue the travel option that would take the least time on any given occasion. · Destinations attract trips on the basis of distance from the trip origin and attributes such as size and attractiveness. · Changes in travel costs to the traveler, such as parking fees and effects of congestion on travel demand, are not usually taken into account. The latter means that these models are not typically sensitive to travel time analysis; literally the assumption is made that trip demand is inelastic with respect to higher costs arising from congestion. Trip-based models present two concerns: (1) nonmotorized transport is not usually taken into account and (2) the models lack sensitivity to chained trips. Chained trips are those that involve multiple stops en route to a destination. These trips are of particular significance when considering project impacts on low-income and some minority populations who may rely on networking more than others for purposes such as child care. By treating trip segments independently, trip-based models fail to reflect that trip decisions made by individuals often are interrelated. On the other hand, the advantages of trip-based models stem from their simplifying assumptions, which allow for the development of standard analysis packages, such as TransCAD, TRANPLAN, and the Urban Transportation Planning System (UTPS) and which make the forecasting procedure affordable to most metropolitan planning organizations (MPOs). The data requirements of trip-based models are less than for activity-based models. Indeed, the simplicity and lower data requirements of these models can be appreciated when making a preliminary assessment of the impact of a transportation project on travel time or congestion levels. Activity-based models In general, activity-based models are still in the developmental stage, but it is likely that they will see increased application in the near future. Testing of early versions of these models has revealed that travel demand forecasts can be developed to treat daily travel patterns in their entirety without breaking them down into individual trips. This is important because attempting to reduce travel to individual trips tends to compromise the interdependencies and continuities that exist across the series of trips made by a given traveler. The testing to date also indicates that activity-based models will be able to predict travel behavior along a continuous time axis and to evaluate specific transportation system changes, such as the impacts of daycare facilities at work, extended transit service hours, or changes in transit lines on travel patterns and demand. Travel Model Improvement Program (TMIP) is developing the Transportation Analysis and Simulation System (TRANSIMS), an integrated system of travel forecasting models that includes a population synthesizer, activity generator, route planner, and traffic microsimulator. The system seeks to create a virtual metropolitan region with a completely disaggregated representation of the population. TRANSIMS simulates the movement of individuals and 170