Transportation

Mega-regions are a new geography that may well form the “nation's operative regions when competing in the future global economy. A challenge is to determine how to foster greater efficiencies in these mega-regions by creating a stronger infrastructure and technology backbone in the Nation's surface transportation system,” according to the March 2010 FHWA Strategic Plan. To meet this challenge these regions will need analysis tools to evaluate scenarios and their regional impacts, analysis tools covering areas larger than covered by the typical Metropolitan Planning Organization (MPO) or State Department of Transportation (DOT) models. This paper describes what makes mega-regions different and identifies analytic issues mega-regions may need to address, identifies the Chesapeake Mega-region and provides a framework for analyzing issues within the Chesapeake mega-region. Finally, the framework is tested through a proof of concept scenario which assumes a sudden price rise in gasoline prices and the likely effects on travel. A brief summary of further work and additional scenarios planned is provided.

Maryland is often referred to as the birthplace of smart growth, a movement in land use planning that contributed to what is now referred to as sustainability planning, sustainable development, and sustainable communities. Maryland adopted a Smart Growth Program in 1997 with the primary purposes being to use incentives to (1) direct growth into areas already developed and having public facilities, and (2) reduce the conversion of farm, forest, and resource land to urban uses.

The National Center for Smart Growth Research and Education at the University of Maryland was established in 2000 in large part because of Maryland’s leadership in the field of smart growth. Its mission is to provide research and leadership training on smart growth and related land use issues in Maryland and in metropolitan regions around the nation. Thus, a key focus of the Center’s research is Maryland’s Smart Growth Program: where is it effective, and how can it be improved?

This report provides some indicators (also called performance measures) that suggest answers to those questions. The term “suggest” is important: (1) there are many limitations of any assessment based on indicators, no matter how well developed, and (2) the indicator assessment reported here is only in its preliminary stages. Understanding the limitations of indicators is critical to interpreting their significance. Thus, Section 2 and Appendix B of this report discuss in some detail data, methods, and limitations.

Researchers and policymakers acknowledge those limitations, but that acknowledgement does not slack their desire for indicators that say something concrete about whether desired outcomes are being achieved, and at what cost in direct expenditures and spillover effects; and about directions for policy that would increase the desired outcomes, reduce the costs, or both. Sections 3 and 4 address those issues.

Section 3 reports indicators for six categories of issues. Population and employment growth drive development. That development is the immediate concern of the two thrusts of the Maryland Smart Growth Program: it puts pressure on the natural areas that the Program wants to protect, and it can occur in development patterns that not only eliminate and vitiate those natural areas, but also are inefficient from the perspective of providing transportation and other infrastructure and, ultimately housing (and other buildings). Some of the key findings:

• Population. The population growth rate in Maryland approximately equals the national average. The indicators give no direct, rigorous, or even casual evidence that the Smart Growth Program either increased or decreased the amount or composition of population growth statewide.
• Employment. Employment and other measures of economic activity have consistently grown over the last two decades in Maryland and all its regions. From 2000 to 2009, Maryland had the 13th highest annualized rate of job growth (1.0%) among the 50 states. Indicator data allow the conclusion that the Smart Growth Program did not stop economic growth, but they do not allow a conclusion about whether the Program increased or decreased that growth from what it would have been in the absence of the Program.
• Transportation. For most measures of transportation performance that are standardized, Maryland looks like other states: VMT, congestion, and car ownership have risen consistently over time. Maryland has higher transit ridership than most states, some of which may be attributable to the Smart Growth Program but most of which is attributable to Maryland’s proximity to Washington, D.C. and its own historical investments in transit (especially in Baltimore and in suburban Maryland) that pre-date the Program.
• Development patterns. Urban development continued in Maryland at densities lower than several comparison states from 1990 to 2000. Most of that growth has not been infill of urban areas: the predominant form of urban development in Maryland remains suburban. Three-fourths of the new single-family acres were developed outside PFAs since 1997. Indicators of Smart Growth in Maryland NCSGRE January 2011 Page 3 While this indicator has shown some improvement in recent years, the share of parcels developed outside PFAs continues to demonstrate an increase over time. Despite increases in density for the state as a whole (which is inevitable if there is any population growth), a substantial amount of Maryland’s new growth has been occurring in the exurban areas of the state. The share of population that lives within a half-mile of rail transit stations, however, has generally risen over time.
• Housing. Although the single-family share of new housing construction has fallen recently, the single-family share of housing in Maryland is high for a highly urbanized state. Housing prices have inflated faster in Maryland than most other states the last few decades, clearly raising questions of affordability, which varies across the state.
• Natural areas. The trends for acres of farm and forest land have been steadily downward in Maryland and the U.S. for a long time, but data suggest that rate of decline is decreasing. Maryland and its counties have protected well over 1.3 million acres of land. There is still, however, a substantial amount and percent of critical land that is not protected. Measures of air quality are mainly stable or improving, yet measures of water quality demonstrate poor conditions in watersheds across the state.

If the indicators here are leaning in any direction, it is that Maryland has not made substantial progress toward improving its performance in many of the areas pertaining to smart growth. There are, however, reasons to qualify a direct conclusion like that one:

• Without the kind of research design that goes well beyond the reporting of indicators into statistical controls for multiple explanatory variables, there is no solid way to rebut the hypothesis that what the Maryland Smart Growth Program did was to prevent many indicators from getting much worse than they are.
• Things take time. Many changes in technology, social attitudes, prices, and the built environment occur slowly. Indicators of Smart Growth in Maryland NCSGRE January 2011 Page 4
• If it is too early to expect to see much by way of results (e.g., changes to trends) then perhaps indicators of outcomes should be supplemented by indicators of inputs: of efforts made to stimulate future change (i.e., the number and strength of policies to change the patterns and effects of growth).

Related Resource

Indicators of Smart Growth in Maryland: Appendices

Emission reduction strategies are gaining greater attention to support the national objective for a sustainable and green transportation system. A large percent of emission contribution arises from transportation modes are primarily from auto and truck travel. Reductions in highway travel require prudent planning strategies and modeling user’s response to planner’s policies. Modeling planning goals and user’s response is a challenging task. In this paper the authors present a joint travel demand and environmental model to incorporate vehicle emission pricing (VEP) as a strategy for emission reduction. First, the travel demand model determines the destination, mode and route choice of the user’s in response to the VEP strategy set by the planner. Second, the emission model provides NOx, VOC, and CO₂ estimates at a very detailed level. A Base-case and three models are proposed to incorporate VEP in a multimodal transportation network. The objective function of the Base-case is the minimization of Total System Travel Time (TST), and the models are designed with the objective of minimizing of Total System Emission (TSE). User Equilibrium method is used for travel to model user responses and solved by Frank Wolfe algorithm. The Base-case represents “do-nothing” conditions and the three models address the interactions between planner’s perspectives and user responses to VEP strategies. The proposed model is applied to Montgomery County’s (located in the Washington DC-Baltimore region) multimodal transportation network. The case study results show that VEP can be used as a tool for emission reduction in transportation planning and policy.

Land use and neighborhood characteristics have long been linked to transit ridership. Large-scale agencies, such as state departments of transportations, often make decisions that affect land use pattern and transit services. However, the interdependencies between them are seldom harnessed in decision-making. In this article, we develop and apply a transit ridership model based on land use and other neighborhood characteristics for an entire state. We then discuss its implications for regional and state-level decision-making. We chose the state of Maryland as our study area. Using a number of criteria, we subdivided the state into 1151 statewide modeling zones (SMZs) and, for each zone in the base year (2000), developed a set of variables, including developed land under different uses, population and employment densities, free-flow and congested speeds, current transport capacities, and accessibility to different transport modes. We estimated two sets of OLS-regression models for the base year data: one on the statewide SMZs dataset and other on subsets of urban, suburban and rural typologies. We find that characteristics of land use, transit accessibility, income, and density are strongly significant and robust for the statewide and urban areas datasets. We also find that determinants and their coefficients vary across urban, suburban and rural areas suggesting the need for finely tuned policy. Next we used a suite of econometric and land use models to generate two scenarios for the horizon year (2030) – business as usual and high-energy price – and estimated ridership changes between them. We use the resulting scenarios to show how demand could vary by parts of the state and demonstrate the framework’s value in large-scale decision-making.

The primary purpose of installing Red Light Cameras (RLCs) is to improve intersection safety by discouraging motorists to cross the intersection when the signal for approaching vehicles turns red. Due to the fear of being fined when crossing an RLC equipped intersection at the onset of the red signal, many approaching vehicles may have a tendency of stopping during the yellow phase. This tendency may impact intersection capacity, which can be significant in congested transportation networks during rush hours, especially when several intersections are equipped with RLCs along a sequence of traffic signals, resulting in a disruption of traffic progression. In order to examine the driver and capacity characteristics at intersections with RLCs and compare them with those without RLCs we develop a binary probit choice model to understand driver's stop and go behavior at the onset of yellow intervals, also known as dilemma zone. Further, in order to capture the impact to intersection capacity at intersections with RLCs we develop a probabilistic computational procedure using data from ten intersection pairs (with and without RLCs) in the Baltimore area. The results indicate that, in general, RLCs reduce the intersection capacity since driver's travel behavior is influenced by the presence of the cameras. Other contributory factors for the so-called capacity reduction, such as driver population (e.g., familiar vs. unfamiliar drivers) and traffic-mix (e.g., trucks vs. passenger cars) characteristics have been left for future works.

Ground level ozone remains a serious problem in the United States. Because ozone non-attainment is a summer problem, episodic rather than continuous controls of ozone precursors are possible. We evaluate the costs and effectiveness of an episodic scheme that requires people to buy permits in order to drive on high ozone days. We estimate the demand function for permits based on a survey of 1,300 households in the Washington, DC metropolitan area. Assuming that all vehicle owners comply with the scheme, the permit program would reduce VOCs by 50 tons and NOx by 42 tons per Code Red day at a permit price of $75. Allowing for non-compliance by 15% of respondents reduces the effectiveness of the scheme to 39 tons of VOCs and 33 tons of NOx per day. The cost per ozone season of achieving these reductions is approximately $9 million (2008 USD). This compares favorably with permanent methods of reducing VOCs that cost $645 per ton per year.

This paper illustrates the application of various forecasting methodologies in constructing multiple scenarios for the state of Maryland using Long term Inter Industry Forecasting Tool that tracks inter-industry outputs at a macro scale, and State Employment Model that disaggregates these outputs to the states. We then use accessibility, land availability and observed relationships of employment categories to distribute employment at a county level. In this paper, we identify the possible advantages and pitfalls of using large scale economic models to drive employment forecasts at the county level. This framework allows for simulating the implications of macroeconomic scenarios such as changes in exchange rates and unemployment levels, as well as local land use and transportation policies on local employment and demographics. In particular, we focus on two scenarios as test cases both of which involve very different ideas about how future might unfold and their effects on land use and transportation policy prescriptions. One of the scenarios involves, among others, rises in health care spending over the next few years and the other involves increases in energy prices. As will be shown, they have different spatial effects and suggest different policy actions on the part of various governments.

Spring of 2007 will mark the 10th anniversary of the passage of Maryland’s Smart Growth and Neighborhood Conservation Initiative; an effort designed to discourage sprawl development, foster more compact communities, protect the best remaining farms and open space in the state, and save taxpayers from the growing cost of providing services and infrastructure to serve far-flung development. Almost before its various provisions took effect in 1997 and 1998, the Maryland initiative generated interest and acclaim across the country. It received numerous awards and became the principal legacy of the program’s primary architect, former Governor Parris N. Glen- dening. Governors in other states, such as New Jersey, Colorado and Massachusetts, instituted their own “smart growth” proposals, often modeled after portions of the Maryland program. Even the popularity and wide usage of the now omnipresent phrase “smart growth” can be attributed in large part to the Maryland program.

But, what has been the effect of Maryland’s Smart Growth pro- gram? Looking at it some ten years later, has it worked? Did it accomplish what it was designed to do? What have been the strengths and weaknesses of the Maryland approach, and how can lessons from the Maryland experience be used to offer a new set of policymakers in Maryland, as well as elsewhere in the nation, practical suggestions on how to make smart growth smarter?

Moving traffic efficiently is something transportation planners should know and care about, because our "customers" (the traveling public) find traffic so frustrating and because competent traffic engineers aren't always around.

This paper presents an empirical examination of the relationship between information and communications technology (ICT) and travel. The primary research objective is to examine the effects of several indicators of ICT usage on three measures of travel outcomes. The ICT indicators include the frequency of Internet use, the number of mobile phones, and the presence of a telephone at home for business purposes. The travel outcomes examined are vehicle miles traveled (VMT), total daily trips, and daily walking trips. Using the 2001 national household travel survey (NHTS) data for Baltimore metropolitan area, a linear regression model is estimated for VMT and two Poisson regression models are estimated for, respectively, total daily trips and daily walking trips. The empirical results suggest simultaneous existence of substitution and complementarity interactions between ICT and travel, with complementarity as the dominant form. Implications of the research findings are discussed.

Can the physical environment determine physical activity levels? Does your place of residence affect your level of physical activity and ultimately your weight and health? There is relatively strong evidence of association between compact development patterns and use of active travel modes such as walking and transit. There is weaker evidence of linkage between compact development, overall physical activity, and downstream weight and health effects.

Since the Publication of ITE's "Traffic Calming: State of the Practice," the field of traffic calming has matured. This feature summarizes a 2004 survey of traffic calming practices in 21 leading jurisdictions. The results are compared to surveys conducted for the national report in the 1990s.

The study reported here was the first to examine the relationship between school location, the built environment around schools, student travel to school, and the emissions impacts of this travel. Students with shorter walk and bike times to school proved significantly more likely to walk or bike—which argues for neighborhood schools. Students who have access to sidewalks along main roads were also more likely to walk—which argues for improvements in sidewalk networks.

Neighborhood schools that can be reached by walking and biking can increase the amount of walking and biking to school, can shorten trip distances,and can reduce motor vehicle emissions significantly.

Visual preference surveys have become a popular tool among planning practitioners. By tapping visual media, such surveys help to illustrate physical design alternatives in ways that words, maps, and other media cannot. They have found applications in visioning projects, design charrettes, and other physical planning activities with heavy public involvement. With little additional effort, a visual preference survey can be restructured as a visual assessment study, which provides more useful information. Confounding variables can be controlled, and underlying qualities that cause certain scenes to be preferred can be identified. This article reports on a visual assessment study of state highways, identifying the physical features that can make them into main streets.

An Expert Land Use Panel was used to forecast the land use impacts of a major highway project in the Washington, DC area, the Inter-County Connector. What makes this panel noteworthy is the fact that a subgroup of panelists, convinced that the accessibility impacts of the highway were not being adequately considered by the majority, developed a simple land use allocation model which they then used to produce independent forecasts. This allows us to compare more intuitive and ad hoc forecasts based only on expert opinion with those based on a formal land use allocation model. At least in this case, the two differed sufficiently to suggest that the two processes are not mere substitutes for one another. This prompts us to recommend that subsequent panels be fed accessibility data early in the process to inform their intuitive judgments, and that simple land use allocation models be considered as a complement to expert opinion.

In this paper, we explore the transportation-land use policy connection. More specifically, we consider the question: can land use policy be used to alter transportation behavior? The answer is of some importance. If the answer is yes, then there is hope that land use policies can be designed and implemented that will bring some relief to the gridlock and complex transportation problems facing US metropolitan areas. This is the underlying assumption behind most smart growth policy reforms. If the answer is no, then land use policy may still be important, but is not likely to play an important role in resolving transportation issues.

We proceed as follows. First we offer a schematic that identifies necessary conditions for land use policy to play a role in addressing transportation issues. Specially,we argue that for land use policy to play an effective role, three conditions must hold.  First, land use must be able to alter transportation behavior. Second, transportation infrastructure must not fully determine land use. Third, the condition on which we consider most extensively, land use policy must significantly and constructively affect land use. After presenting the schematic, we consider the evidence on each of these conditions. Based on our review of the evidence, we conclude that land use policy can play an effective role in addressing transportation issues, but that the role is likely to be small, often counter productive, and most effective at the neighborhood scale.

In February of 2002, as aquifers, streams and reservoirs in many parts of Maryland reached record lows, 72 members of the state's General Assembly signed a letter to the then-Governor Parris Glendening requesting the creation of a special commission to investigate ways of stemming the decline of water supplies. A year later, Governor Robert Ehrlich signed an executive order creating a Water Resource Management Advisory Committee. Among other activities, that committee is directed to review ongoing scientific research on climate change and its regional impacts on water sources; assess the adequacy of current governmental laws, policies, regulations, resources, regulatory enforcement and monitoring programs directed to water resource management, development, conservation and protection in the State; and make recommendations for the actions needed (and the associated costs and funding alternatives) to ensure that the State’s water resources are used “in a manner consistent with their long-term sustainable use and protection.”

The research investigates how Asian and Latino immigrants’ prior urban experiences can inform the future planning and growth of suburban communities in Maryland. The investigation of Maryland immigrants’ various built environment (dwelling, landscape, neighborhood, transportation mode) preferences will result in a set of ecologically appropriate and culturally sensitive design guidelines that will help shape the future of the rapidly growing suburban communities.

Pedestrian safety is emerging as a major area of concern for MPO's and planning agencies. Typically, pedestrian safety has been analyzed by either examining the absolute number of pedestrian crashes at a location, or computing an exposure rate from the number of crashes and the traffic volume. A more desirable measure would be an exposure rate based on the pedestrian volume, but it has not proven feasible to obtain pedestrian flow volumes on a widearea basis to support this analysis. This report describes a pedestrian flow modeling process that was developed under the sponsorship of the Maryland DOT and the University of Maryland National Center for Smart Growth. The process provides micro-scale daily pedestrian flows on all sidewalks and crosswalks in a substantial coverage area. Two test cases were analyzed: an urban scenario comprising about 10 square miles of downtown Baltimore, and a suburban scenario comprising about 15 square miles of Langley Park in Prince Georges and Montgomery Counties.

Joel Garreau's book "Edge City" made Tysons Corner synonymous with auto-centric sprawl, yet the Tysons Corner Comprehensive Plan aims to transform the area into a pedestrian- and transit-friendly downtown for Fairfax, Virginia. This report by Distinguished University of Maryland Professor, Richard Etlin, proposes 15 recommendations to improve upon the comprehensive plan and realize a new vision for development in Tysons Corner.

Editorial published in the "Journal of Epidemiology & Community Health" on the future of collaboration between public health and urban planning professionals.

The relationship between travel behavior and the local built environment continues to be a contentious issue, despite several research efforts in the area. The current paper investigates the significance and explanatory power of a variety of urban form measures on nonwork activity travel mode choice. The travel data used for analysis is the 1995 Portland Metropolitan Activity Survey conducted by Portland Metro. The database on the local built environment was developed by Song (2002) and includes a more extensive set of variables than previous studies that have examined the relationship between travel behavior and the local built environment using the Portland data. A multinomial logit mode choice model results indicate that higher residential densities and mixed-uses promote walking behavior for nonwork activities.

Travel and Environmental Implications of School Siting, released by the EPA on October 8, 2003, is the first study to empirically examine the relationship between school locations, the built environment around schools, how kids get to school, and the impact on air emissions of those travel choices. Over the next few decades, communities making decisions about the construction and renovation of thousands of schools will be challenged to meet multiple goals -- educational, fiscal, and environmental. The study finds that:

School proximity to students matters. Students with shorter walk and bike times to school are more likely to walk or bike.

The built environment influences travel choices. Students traveling through pedestrian-friendly environments are more likely to walk or bike.

Because of travel behavior differences, school location has an impact on air emissions. Centrally located schools that can be reached by walking and bicycling result in reduced air emissions from driving.

More data collection and research are needed to add further to the understanding of these effects. Specifically, improved data about both school travel and the built environment as well as new modeling techniques can build on these results.

For some time, there has been a trend toward construction of big schools and requirements for large sites. Guidelines, recommendations, and standards that encourage or require building large schools on new campuses or discourage renovation are embedded in a variety of state and local regulations, laws and funding formulas. This study provides important information about the effect of school location on how children get to school. It shows that school siting and design can affect choices of walking, biking, or driving. In turn, these changes in travel choices could affect traffic congestion, air pollution, and school transportation budgets.

As in many countries around the world, concerns about contemporary urban development patterns and their effects on the natural and social environment are high and rising in the United States. Though these concerns are not new, the recent period of sustained economic growth has led to both rapid urban expansion and falling relative concerns about other problems like crime, unemployment, and government deficits. Urban sprawl is now a major public policy issue (U.S. Office of Technology Assessment 1995, U.S. General Accounting Office (GAO) 1999, GAO 2000).

How to address -- even define -- the problem, however, remains unresolved and contentious. Some view urban sprawl as a major threat to environmental quality, fiscal stability, and human health. Those with this point of view support policy reforms sometimes called smart growth, new urbanism, and sustainable development (Ewing 1997, Smart Growth Network 2002). To others, sprawl is simply the result of increases in population, rising real incomes, and the expression of consumer demands (Brueckner 1999). To those with this point of view, there is little evidence that urban sprawl has adverse social or environmental consequences or warrants a policy response (Gordon and Richardson 1997, Urban Futures 2002). In a nation rich in land resources and steeped in traditions of private property rights, this view is not easily dismissed.

For many years, neighborhoods have been classified as either “suburban” or “traditional.” But new homes today are built in many different types of neighborhoods with many different design features. In this paper, we develop a quantitative method for classifying the neighborhoods of new homes in the Portland metropolitan area. We proceed in three steps.  First we measure urban form attributes of neighborhoods around newly developed homes.  We then use factor analysis to identify a small set of factors that capture essential differences in urban form. Finally we use cluster analysis on these factor scores to identify distinctly different neighborhood types. Applying these methods to neighborhoods around new single family homes in the metropolitan Portland, Oregon, we are able to identify eight factors of urban form and six neighborhood types. We then show that most new single family homes in metropolitan Portland are built in new suburban neighborhoods but a substantial portion is occurring in traditional urban neighborhoods.