The National Center for Sustainable Transportation (NCST) is one of five national centers funded by the U.S. Department of Transportation’s University Transportation Centers (UTC) Program, and the only national center focused on the Fixing America’s Surface Transportation (FAST) Act research priority area of Preserving the Environment. UC Davis leads the NCST consortium, with partner centers at CSU Long Beach, UC Riverside, USC, Georgia Tech, and the University of Vermont.
The Effect of Land Use Policies and Infrastructure Investments on How Much We Drive: A Practitioner’s Guide to the Literature
A number of state governments have recently passed legislation aiming to rein in vehicle miles traveled (VMT), and many cities have begun to take action to reduce VMT in their jurisdictions. Policymakers often want to know what they should do to encourage less driving. Unfortunately, there is no “one size fits all” solution. The effectiveness of various policy options depends critically on context: who is driving, where are they going, and what alternative modes and destinations are available.
Fortunately, there is an extensive body of academic literature on this topic that practitioners can tap into when considering various policy options. This policy brief summarizes findings from the white paper examining this literature.
Parking has long been an urban planning challenge. Providing parking in city centers is land-intensive and expensive. Moreover, drivers searching for scarce parking can increase congestion, vehicle miles traveled (VMT), and greenhouse gas (GHG) emissions. Use of automated vehicles to drop off and pick up travelers could reduce the demand for parking, which could reduce VMT and associated emissions and allow urban spaces currently used for parking to be converted to more beneficial uses. However, automated vehicles could also have negative consequences. They could generate empty vehicle travel and more cross-traffic movements due to drop-offs and pick-ups which could increase congestion, VMT, and GHG emissions.
Researchers at the University of California, Davis modeled the travel effects of changes in drop-off and pick-up activity and parking supply that might be triggered by widespread automated vehicle use in San Francisco’s city center. A primary goal of this research was to determine an optimal level of automated vehicle adoption that minimizes negative consequences. The researchers also modeled methods to control these negative consequences, including expanding drop-off and pick-up zones and imposing auto pricing policies to curb demand. This policy brief summarizes the findings from that research and provides policy implications.
One of the most notable recent trends in U.S. metropolitan areas is the rapid growth in warehousing and distribution (W&D) activity. The number of warehousing establishments increased 15%, and warehousing employment increased 33% between 2003 and 2013. At the same time, some operations in some markets appear to be decentralizing (moving away from the central core to the urban peripheries) in search of lower land costs.
Although decentralization may contribute to reduced total freight shipping cost, increased distance from urban centers may result in increased truck vehicle miles traveled (VMT) and associated externalities: congestion, increased fuel consumption, noise, greenhouse gas (GHG) and criteria emissions, accidents, and infrastructure damage. While the logistics business benefits from cost savings, society at large incurs any additional external costs.
Understanding how these shifts are affecting truck VMT is essential for developing effective policies for managing truck activities and their associated externalities. Due to the dearth of truck shipment data, this research focuses on the changes in W&D facility and employment location and uses measures of relative location to infer potential truck VMT impacts.
Renewable Natural Gas (RNG) is an important alternative fuel that can help the State of California meet several greenhouse gas (GHG) reduction and renewable energy targets. Despite considerable potential, current RNG use on national and state levels are not significant. RNG production potential in California through thermochemical conversion was evaluated as part of this project by assessing technical biomass availability in the state. Biomass feedstocks are defined broadly and include most carbonaceous matter including waste. The types of waste biomass available in the state are classified into three categories: municipal solid waste (MSW), agricultural residue and forest residue. A total of 32.1 million metric tonnes per year (MMT/year) of biomass is estimated to be technically available in the state. The energy content of this biomass is equivalent to approximately 602.4 million mmbtu/year. A survey of current renewable electricity generation and curtailment trends in California was conducted. Real-time data show significant curtailment throughout the year totaling more than 1,300 GWh from 2016 to early 2019. Power to gas and other forms of long-term storage integrated into the electric grid can mitigate these losses and enable smooth integration of additional renewables into the grid. Oxygen/air blown gasification, hydrogasification and pyrolysis are the three major technology options available for thermochemical biomass conversion to a gaseous fuel, including RNG. Although there are no commercial thermochemical biomass to RNG conversion facilities in operation, a number of gasification and pyrolysis technologies are undergoing pilot scale demonstration and development. Design basis for two thermochemical and power to gas conversion projects were developed as part of this project. Life cycle and economic analysis were conducted for the recommended processes.
This research informs metropolitan land use planning by studying a heretofore understudied variation of land use – travel behavior interactions: how access to jobs in employment sub-centers influences household vehicle miles traveled (VMT) in the five-county Los Angeles Combined Statistical Area (CSA). The authors used data from 2009 National Employment Time Series to identity employment sub-centers and data from the 2012 California Household Travel Survey to measure household VMT. The authors then modified a standard land use – travel behavior regression to include, as explanatory variables, measures of access to jobs that are in and not in employment sub-centers. Their results shows: (1) Accessibility to jobs outside employment sub-centers often has a larger impact on VMT than the accessibility to jobs inside the subcenters. (2) The effect of accessibility on household VMT varies in core counties and periphery counties. (3) Accessibility to jobs within 5 miles from a household’s residence has a larger association with household VMT than accessibility to jobs beyond 5 miles from the residence. (4) Moving a representative household from the centroid of Moreno Valley in Riverside County to the centroid of Koreatown in Los Angeles is associated to a 46.6 percent reduction for household-level VMT.
The freight system is a key component of California’s economy, but it is also a critical contributor to a number of externalities. Different public agencies, private sector stakeholders, and academia engaged in the development of the California Sustainable Freight Action Plan (CSFAP). This plan put forward a number of improvement strategies/policies. However, the freight system is so complex and multifaceted, with a great number of stakeholders, and freight operational patterns, that evaluating or assessing the potential impacts of such strategies/policies is a difficult task. To shed some light, this project develops a freight system conceptualization and impact assessment framework of the freight movements in the State. In doing this, the framework assesses the impact of commodity flows from different freight industry sectors along supply chains within, originating at, or with a destination in the state of California.
The conceptual framework analyzes the freight flows in supply chains, and the type of freight activity movements and modes. The framework uses a Life Cycle Assessment (LCA) Methodology. The framework could be extended to support multidimensional cost/benefit appraisals for both direct benefits (e.g., delays, costs, accidents, maintenance) and social benefits to non-users which include impacts on regional and national economies as well as environmental and health impacts. This report discusses the main components of the conceptual framework based on a comprehensive review of existing methodologies. The implementation is limited to the Life Cycle Impact Assessment (LCIA) following the Environmental Protection Agency’s Tool for Reduction and Assessment of Chemicals and Other Environmental Impacts (TRACI).
The report describes the results from the LCIA implementation for a number of case studies. Specifically, the work estimated the impacts of moving a ton of cargo over a mile for various industry categories and commodity types. These results show the relative difference across industries and commodities and could serve to identify freight efficiency improvement measures in the state of California.
In the early years of transportation planning and highway infrastructure development in the United States the focus was on intercity or long-distance travel, a contrast to the metropolitan travel and state-based models that dominate today. Daily home and work-based travel, which have been the focus of data collection and models since the 1950s, are well-modeled by regional agencies and a limited number of state travel demand models even include some long-distance travel. Nonetheless, long-distance travel demand and factors affecting behavior are not thoroughly considered in transportation planning or behavior research. Only one recent activity-based model of national travel demand has been created and its scope was limited by a severe lack of data. The conceptualization of models to consider intercity long-distance travel has changed little since its inception in the 1970s and 1980s. In order to comprehensively consider transportation system sustainability, there is a critical need for improved nation-wide annual overnight activity data and models of overnight travel (a re-focus and important distinct re-framing of long-distance trips that this white paper suggests).
Truly addressing the economic, environmental, and social equity issues required to create a sustainable global transportation system will entail completely updating our existing planning framework to meaningfully include long-distance travel. It is clear that long-distance passenger miles must be accounted for when addressing greenhouse gas (GHG) emissions and other negative environmental externalities. Less well-known are the questions of social justice that loom large when one considers the details of long-distance travel. Travel in our society is becoming increasingly associated with quality of life. Those without intercity access may miss opportunity and social capital. However, without representative long-distance travel data it is impossible to compare the relative participation by different groups and to consider latent demand. It is difficult to measure who comprises the global mobile elite and who lacks sufficient intercity mobility for reasonable social network obligations and personal services.
This white paper suggests utilizing a common framework for long-distance data collection and tabulation that re-defines long-distance travel into daily or overnight. The author advocates using overnight as the defining characteristic for data collection, which complements existing daily travel surveys already capturing long day-trips. Within frameworks moving forward it is important to clearly characterize all trip purposes, including mixed purposes and purposeless travel, which comprise an appreciable portion of long-distance travel. Spatial data that distinguish between simple out-and-back trips and spatially complex trips are necessary and mobile devices have now made this measurement of long-distance tours feasible. In order to truly model all travel in the current system, we must move away from the idea that most travel is routine, within region, and home-based. Many people, especially the most frequent travelers, have long-distance routines including multiple home bases. Additionally, our models should not assume that travelers staying at a second home, hotel, or friend’s home travel like residents. Efforts to measure and model non-home-based travel or travel at destination are essential to accurately modeling behavior. Daily surveys such as the 2017 National Household Transportation Survey are increasingly doing this. A nation-wide annual activity model of overnight travel must fully incorporate both surface and air travel to allow full consideration of alternative future system scenarios.
Cars provide an unparalleled level of mobility but have negative financial, public health, environmental, and social impacts. Reducing the need for driving in California would produce a range of household- and community-level benefits. Driving is associated with adverse health effects (e.g., obesity, high blood pressure, depression, injuries, fatalities), while commuting by walking or biking provides numerous physical and mental health benefits. A reduction in driving would also improve public health by decreasing air pollution and greenhouse gas emissions. It would save substantial sums of money: households spend about $9,000/year or 16% of their expenses on private vehicle ownership (2017 data) and the state spends over $500 million per year on highway maintenance. A less car-dependent society would also be more equitable for those with limited income or limited physical abilities who cannot drive, to the benefit not just of those individuals but the community as a whole. While it is not realistic in the foreseeable future for most Californians to live without their cars, it is possible to decrease car dependence. Doing so requires a shift away from a century-old prioritization of the goal of reducing vehicle delays over other important goals. Creating a less car-dependent world is not necessarily more costly to the public and can be achieved over time through changes in land use and transportation planning practices. Answers to many of the frequently asked questions about such efforts are provided.
Examining the Safety, Mobility and Environmental Sustainability Co-Benefits and Tradeoffs of Intelligent Transportation Systems
In this whitepaper, the authors briefly describe the three major MOEs, followed by a categorization summary based on the most recent literature. Next, a number of typical CAV applications have been examined in depth, providing a detailed analysis of the different MOEs co-benefits and tradeoffs. Further, three representative CAV applications have been examined in detail in order to show the association between the application focus and tradeoffs/co-benefits of different performance measures. The CAV applications include High Speed Differential Warning (safety-focused), Lane Speed Monitoring (mobility-focused), and Eco-Speed Harmonization (environmental impacts-focused). The authors then highlight several future research directions, including the identification of key influential factors on system performance and how to obtain co-benefits across all key MOEs. The overall intent of this whitepaper is to inform practitioners and policy makers on the potential interactions between the safety, mobility, and environmental sustainability goals of implementing specific CAV applications as part of their ITS programs.
Related Research Centers & Groups
- 3 Revolutions Future Mobility Program
- China Center for Energy and Transportation
- Energy Futures Research Center
- Hydrogen Pathways Program
- Plug-In Hybrid & Electric Vehicle Research Center
- Sustainable Freight Research Center
- Sustainable Transportation Center
- Sustainable Transportation Energy Pathways (STEPS)
- University of California Pavement Research Center
- Urban Land Use and Transportation Center
- Policy Institute for Energy, Environment, and the Economy
- UC Davis Institute of Transportation Studies