UrbanSim Analysis

Bay Area UrbanSim is the Metropolitan Transportation Commission’s (MTC’s) regional land use model. The model is used to analyze how planning policies affect the location choices of households, businesses, and real estate developers over the long term (i.e, 20 to 30 years). In addition to the methodology and results presented below, Appendix A outlines additional model assumptions.

UrbanSim was used to model reduced or eliminated minimum parking requirements over a 15-year simulation period to analyze a forecast for the location and type of development throughout the region in that timeframe. The implementation was designed in such a way that the assumptions can be adjusted and simulations rerun to analyze the sensitivity of development to changes in parking requirements. Three simulations are modeled, including:

1. A baseline scenario where parking requirements are set and do not change throughout the region,
2. A reduced requirement scenario where parking minimum requirements are halved within Transit Priority Areas (TPAs) and remain constant outside TPAs, and
3. An eliminated requirement scenario where parking minimum requirements are set to zero within Transit Priority Areas (TPAs) and remain constant outside TPAs.

Methodology

Data

There is an existing UrbanSim implementation in the Bay Area, which was developed for the 2014 Bay Area regional plan – Plan Bay Area – and associated Environmental Impact Report. For the existing implementation, the necessary parcel, building, household, and employment data are already available. Existing model specifications for residential and non-residential prices, as well as household and employment location choice models are also available. As the next Regional Transportation Plan (RTP) for the Bay Area is due in 2017, and UrbanSim is slated be a key component in testing alternative land use scenarios for the new plan. These model configurations are still subject to change for the next policy implementation.

New data has been collected regarding typical baseline parking requirements in the 101 Association of Bay Area Governments (ABAG) jurisdictions,[1] but data for only around 50 of the cities is readily available at this time. In order to address Policy Question #2 for the VPP Parking Project, baseline parking requirements are assumption-based, as data specificity is insufficient to claim parcel-level understanding of parking requirements throughout the Bay Area. In this way, the assumptions can be simply and transparently communicated to stakeholders.

Parking Requirement Assumptions

Parking requirements are defined for either residential, industrial, office, or retail building types. Parking requirements are per unit for residential uses and per 1000 square feet for non-residential uses. Current parking requirement assumptions for the “no project” scenario are specified by the project team,[2] based on parking requirement data for 50 cities within the Bay Area. Using the data from these 50 cities, the mean upper-minimum parking requirements for each land use type are used to create a reasonable default to represent regional average parking requirements (with the exception of San Francisco, where requirements are set lower).[3] These averages are rounded to the nearest 0.5 spaces. Therefore, region-wide parking requirements are 3.0 spaces per residential unit (for San Francisco 1.0 spaces per residential unit); 4.5 spaces per 1,000 square feet of retail space; and 4.0 spaces per 1,000 square feet of office space.

With these assumptions, parking requirements will vary by building type but not by jurisdiction (with the exception of the City of San Francisco). If data on minimum parking requirements improves in the future, parking requirements can be specific to jurisdictions or even within jurisdictions, as the UrbanSim simulation is entirely parcel-based (with some residential unit level representation also available).

Scenarios

The assumptions specified by building type and density were applied to all proposed developments in the region. The modeling process includes a baseline “no project” simulation to compare scenario results to. The second scenario will reduce parking requirements by half within Transit Priority Areas (TPAs). For the third scenario, parking requirements will be reduced to zero. TPAs are used as the basic geography for reduction of parking requirements, as a reasonable assumption is that parking requirements cannot be reduced without meeting transportation demand with some other mode, most likely transit and non-motorized modes in the dense built environments around transit hubs.

Summary of Results

The relative amount of growth within areas where minimum parking requirements were reduced in Transit Priority Areas (TPAs) was calculated in order to interpret change in minimum parking requirements from simulations. TPAs represent approximately half percent of the land area in the Bay Area. The results of the scenarios are represented by the percentage of residential and non-residential growth in built space inside and outside of TPAs, for residential and non-residential separately. In other words, given that we are assuming population and job growth to be constant across scenarios, the number of net residential units and net job spaces is roughly constant across scenarios as well. The simple metric of how much of that growth falls within TPAs for each of the three scenarios is a first estimate at the global impact of the reduction in parking on changes in the built environment. These simple summaries are provided below.

The baseline model predicts that 73.2 percent of residential growth and 60.0 percent of non-residential growth will occur in TPAs throughout the nine-county San Francisco Bay Area region. When parking requirements are reduced by one-half, the amount of residential growth within the TPA increases by 2.2 percent; non-residential growth within the TAP increases by 3.1 percent. Similarly, when requirements are completely eliminated, both residential and non-residential growth within the TPAs increase by 3.5 percent and 5.8 percent, respectively. The reduction due to reducing requirements by one-half has an incrementally larger impact relative to eliminating parking requirements, indicating there is a small nonlinear effect on the reduction in parking.

Table 1: UrbanSim Model Results from Parking Minimum Requirement Scenarios

	Residential Growth			Non-residential Growth
	In TPA	Out TPA		In TPA	Out TPA
Scenario 1	73.2%	26.8%	Scenario 1	60.0%	40.0%
Scenario 2	75.4%	24.6%	Scenario 2	63.1%	36.9%
Scenario 3	76.7%				.2%

UrbanSim Limitations

As with most regional simulations, the accuracy of data is the first and foremost limitation of the study. Many data issues exist in the baseline UrbanSim data, especially the parcel, zoning, and building data, and data cleaning is already the main objective of a current UrbanSim work. In addition, as already discussed, the data on parking requirements is only available for about half of the Bay Area jurisdictions and none of this data involves information at a parcel-scale zoning level. As such, the scenarios described in this document are assumption-driven using reasonable assumptions for current conditions and potential reductions in parking requirements. Although the results of the simulations will not be parcel-accurate, the results are applicable to policy-oriented debates currently taking place in the Bay Area.

Second, as the UrbanSim model is in the middle of a production run which won’t be delivered until 2017, numerous improvements will take place in the coming years that are not currently complete. The improvement to the base year built environment already mentioned is one important improvement, as well as an improvement in non-residential price data and associated statistical models. At this time, non-residential rent data and models are not as accurate as the analogous residential models. Additionally, the current model system has not been calibrated and validated to current observed trends. This work will be performed in the next two years, and the parking simulations can be rerun to check for any changes due to these improvements in the model.

Finally, there are a few assumptions that are made in the pencil out pro formas that should be acknowledged. For instance, specifications that are developed in actual real estate markets, such as residential unit types (1 bedroom, 2 bedroom, and 3 bedroom) and factors of building design including earthquake zones, high slopes, etc. are not represented. Nonetheless, it is thought that the UrbanSim pro forma is a best practices model of residential development and sufficient for the analysis described in this document.

Most relevant to this project is the fact that reducing parking requirements are assumed to reduce parking. This is an assumption that must be made because of poor observed data on the willingness of people to pay for parking when it is not required. In other words, it is clear that even in the case of no parking requirements, some parking will be built anyway because many people are willing to pay for it. At this time, quality empirical data on how many people will pay for parking and how much they would pan in various situations is not at all clear. For now, an assumption of the amount of parking that will be built is used, rather than trying to predict the demand for parking (in terms of the willingness to pay) with insufficient information.

[1] The ABAG jurisdictions consist of 101 cities and towns within the nine-county Bay Area region.

[2] VPP Parking Project team members from Synthicity, CDM Smith, and the Metropolitan Transportation Commission (MTC)

[3] Baseline parking requirements were set to the same level throughout the region, with the exception of San Francisco’s residential requirements because its policies for lower requirements make it a significant outlier.