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Tool Summary Tool Characteristics Tool Application Source of Tools Opinion of Tools

Tool application

Name of the tool
Toolbox for Regional Policy Analysis

Who applied the tool in the case?

The website contains a number of case studies (organised by impact or policy) that have used the toolbox. The information on the two examples come from straight from the website.

The case study of Albany New York illustrates the application of a basic land use model to assess the affects of potential land use shifts on congestion. The Capital District, a four-county region surrounding Albany, New York, has experienced dramatic growth in vehicle-miles of travel (VMT) in recent years, which has far outstripped population growth. One cause of this rapid growth in VMT has been the dispersal of population and employment. While congestion had not yet represented a major threat to the area, future traffic increases were projected to increase traffic delay greatly and to affect transit and freight movement negatively.

Participants in the area's recent "New Visions" long-range transportation planning process expressed concerns over these trends and, in particular, over the transportation impacts of current and projected development patterns. In response, the Capital District Transportation Committee (CDTC), the metropolitan planning organization (MPO) for the Albany region, developed and applied a land-use "pivot" model. The model was applied to test the impacts of transportation actions, tax policies, zoning changes, and urban reinvestment on regional settlement patterns and mobility.

The results of the land use analysis showed that congestion by itself was likely to have a relatively small impact on regional settlement patterns. They also showed, however, that policies to encourage urban reinvestment could have a significantly positive impact on the transportation system. Traffic congestion and delay could also be reduced by locating new development in areas where excess highway capacity exists, away from critical congestion corridors.

This case study illustrates how a basic land use model can be applied, with relatively little effort, to expand the range of policies and impacts that are considered in the transportation planning process.

The second case study comes from Sacramento, California. This case study compares the use of a state-of-the-practice travel demand model and a transportation-land use model to assess regional transportation and land use policies. The results suggest that the land use model captures important feedback relationships not captured by the travel demand model alone.

A multiyear project at the University of California-Davis has compared the use of a regional travel demand model, SACMET96, with two transportation-land use models, MEPLAN and TRANUS, for testing regional transportation and land use policies. The project has evaluated a range of policies, both individually and in combination, including:
• High-occupancy vehicle (HOV) lanes;
• High-occupancy toll (HOT) lanes;
• Light rail transit (LRT) and other advanced transit;
• Transit-Oriented Development (TOD);
• Roadway-Oriented Development (ROD); and
• Pricing.

Impacts were measured for the years 2005 and 2015 on travel, emissions, user benefits, and the spatial distribution of population and employment. The results of the modeling are not always intuitive. Some of the major findings for the Sacramento region include:
• Accounting for land use effects can have significant impacts on forecast vehicle-trips, VMT, congestion, and emissions. Travel and emissions impacts were found, in general, to be significantly greater in MEPLAN than in SACMET96 for comparable policy scenarios.
• Some policies are synergistic while others may work at odds. For example, transit and pricing policies had little impact individually but a more significant impact in combination. While parking pricing had the effect of reducing trip lengths and VMT, it also provided a disincentive to transit station area development and thus had little impact on mode share.
• Similar to transit investments, HOV and HOT policies were found to be much more effective when applied in conjunction with land use and/or pricing policies.
• Positive economic user benefits were found for most scenarios. When applied by income group, the user benefit measure could be used to assess the equity implications of each scenario.

Time taken to fully apply the tool
Not specified

Any other interesting information about the tool

Case study/ies where tool is in use