A major obstacle to incorporating smart growth principles into a community's planning process or assessing the impacts of a smart growth development proposal is the shortage of data and methods for quantifying the effects of smart growth. Critical decisions should not be based solely on logical opinions or anecdotal evidence that smart growth can reduce impacts and improve quality of life. It is important to objectively evaluate the social, economic and environmental consequences. While communities vary in the degree of emphasis they place on different criteria, the most effective and widely-used performance indicators are described below.

Measuring Mobility and Travel-Related Impacts

1. Vehicle Trips per Household
2. Vehicle Miles Traveled
3. Transit Mode Share
4. Walk and Bike Mode Share
5. Travel Time
6. Hours of Congestion
7. Multi-Modal Level of Service

Smart Growth Characteristics that influence Mobility and Travel Impacts

1. Transit Proximity
2. Density of Development
3. Diversity of Development
4. Design of Development
5. Destination Accessibility of Development

Evaluation Methods

1. 4D Indices
2. 4D-Enhanced Travel Forecast Models
3. Direct Transit Ridership Models
4. Multi-Modal Simulations
5. SUMMIT Evaluation of System User Benefits

Evaluation Criteria related to Mobility and Travel Impacts

Vehicle Trips per Household: Smart Growth communities enable residents to substitute walking, bicycling and transit trips for some auto trips. Quantifiable reductions in traffic generation result from specific Smart Growth characteristics, including density, mix of land uses, urban design and location within the region. These vehicle trip reductions can translate to reduced traffic impacts, reduced road-building and infrastructure cost, reduced energy consumption and reduced auto engine starts, which create certain types of air pollution.

Vehicle Miles Traveled per Household: Infill development enables residents to substitute short trips for the much longer trips taken by residents of communities on the urban fringe. This indicator quantifies the reduction in overall traffic demand that comes from substituting infill projects for an equal number of suburban residences. It is also indicative of per-capita production of distance-related auto emissions.

Transit Mode Share: shows the extent to which non-auto trips are substituted for auto trips.

Walk and Bike Mode Share: indicates the extent to which non-motorized travel options are viable and vehicular travel is reduced.

Travel Time: Comparative “before and after” travel times for representative trips.

Hours of Congestion: Hours per day that highway and arterial traffic travels below posted speed.

Multi-Modal Level of Service: Transportation Level of Service (LOS) is a measure of freedom from travel delay, discomfort and inconvenience. Transportation system evaluations usually focus on LOS for vehicles only. Occasionally, LOS is also considered for transit users, pedestrians, or cyclists. Multi-modal LOS is an approach that considers and attempts to balance LOS for users of all modes (auto, transit, bike and walk), with composite benefit or LOS “weighted” or proportioned by the relative number of users of the mode.

Smart Growth Characteristics that influence Mobility and Travel Impacts

Transit Proximity: Number of jobs and residents within ½ mile walking distance of transit.

Density of Development: Higher numbers of residents and jobs per acre are often a Smart Growth planning objective, and are effective at reducing travel and other impacts, especially when accompanied by high levels of regional accessibility, mix of uses, and quality urban design. Development density is useful indicator of Smart Growth plans, and is usually measured in terms of total population and employment per acre. Density also reduces the need to convert exurban land to urban uses.

Diversity of Development: Land use mix measures the relative balances of jobs and housing as well as the mix of retail and non-retail jobs within walking/ biking distance or, secondarily, short driving distance. Diversity is correlated with reductions in vehicle trips and vehicle miles, and is therefore an indictor of a Smart Growth plan.

Design of Development: Smart Growth concepts often involve walkable neighborhoods. When measured in terms of connectivity and density of the street and pedestrian networks and sidewalk completeness, walkable urban designs are correlated with reduced vehicle travel, and represent a useful indicator of Smart Growth.

Destination Accessibility of Development: Infill development places growth at locations with high accessibility to all other activities in the region, an important Smart Growth strategy. Once consequence is reduced vehicle travel per capita. Measuring a plan's accessibility to regional destinations provides a useful indication of Smart Growth.

Evaluation Methods

4D Indices: 4D indices translate a land use plan's density, diversity, design and destinations ratings, through use of research based elasticities to reductions in vehicle trips and vehicle miles per capita. As a result, the 4D indices are measures of Smart Growth. 4D indices can be applied in spreadsheet form to measure the effectiveness of a Smart Growth plan in reducing trip generation. 4D indices are used in interactive community visioning processes. The 4D's are often expressed in terms for elasticities, which express the percentage change expected in trips or vehicle miles per 100% change in density, diversity, design, or destinations. Sample 4D elasticities are provided below.

Sample 4D Elasticities from Synthesis of National Research

The table shows that, for example, doubling residential density (a +100% change) would reduce per-household vehicle trips by about 4%. Elasticities are additive, so that 100% increases in density and diversity and design and destinations can reduce vehicle trips by 15%.

4D-Enhanced Travel Forecast Models: The 4D indices can also be applied in concert with a conventional regional travel demand model to translate a plan's density, diversity, design, and destinations characteristics into estimates of vehicle trips, vehicle miles of travel, mode choice and traffic volumes. This method involves integrating the 4D elasticities into the adopted regional travel model employed by MPO's and many counties, cities and other agencies. Integrated 4D travel models are often used in community Smart Growth visioning processes.

Direct Transit Ridership Models: Transit modeling is often done in a manner similar to road traffic forecasting, by comparing routes through a network to go from an origin to a destination. Studies have shown, however, that the walking or parking conditions at either end of the trip are often more influential on transit usage as the line haul. This means that transit ridership to and from a proposed station can be forecast based on the characteristics of the area around the station. These “direct ridership” forecasts use correlations between land uses and design characteristics of existing stations and the ridership at those stations to predict how changes in land uses, such as replacing a parking lot with a TOD, will affect ridership.

Multi-Modal Simulations: Sophisticated modeling tools are available that analyze multi-modal travel corridors in great detail and present in a highly understandable, visual fashion. Models such as VISSIM analyze the interactive effects of traffic, transit, and pedestrians along streets and at intersections and show, through video displays, the effects on queuing, congestion, and delay for users of each mode. Such models are effective tools for understanding the effects on user experience likely to result from changes such as reducing traffic lanes, slowing speeds, installing roundabouts, or adding bus rapid transit.

SUMMIT Evaluation of System User Benefits: The Federal Transit Administration uses a tool named SUMMIT to evaluate proposed rail transit projects consistently from city to city. SUMMIT sums the benefits experienced by all travelers if a major transit investment is implemented, rather than a low-cost service improvement option. The result is the regional benefit of the major investment. Thematic mapping of results shows the population segments expected to experience user benefits and indicates the travel time benefits to transit users and benefits non-transit users resulting from reduced congestion.