BASSTEGG (Bay Area Simplified Simulation of Travel, Energy, and Greenhouse Gases): Sketch Planning Charrette/GIS Models for Predicting Household Vehicle Miles of Travel (VMT) and Greenhouse Gas (CO2) Emissions

This paper examines the relationship between income, vehicle miles traveled (VMT), and greenhouse gas (GHG) emissions for households with varying access to rail transit in four metropolitan areas—Los Angeles, the San Francisco Bay Area, San Diego, and Sacramento—using data from the 2010–2012 California Household Travel Survey. Daily vehicle GHG emissions are calculated using the California Air Resources Board’s 2014 EMFAC (emission factors) model. Two Tobit regression models are used to predict daily VMT and GHG by income, rail transit access (within or outside 0.5 miles of a rail transit station in Los Angeles and the Bay Area, and linear distance to rail in San Diego and Sacramento), and metropolitan area. Comparing predicted VMT and GHG emissions levels, this paper concludes that predicted VMT and GHG emission patterns for rail access vary across metropolitan areas in ways that may be related to the age and connectivity of the areas’ rail systems. The results also show that differences in household VMT due to rail access do not scale proportionally to differences in GHG emissions. Regardless, the fact that GHG emissions are lower near rail transit for virtually all income levels in this study implies environmental benefits from expanding rail transit systems, as defined in this paper.

The effect of residential location on vehicle miles of travel, energy consumption and greenhouse gas emissions: Chicago case study

The impact of metropolitan, county, and local land use on driving emissions in US metropolitan areas: Mediator effects of vehicle travel characteristics

Leaving level-of-service behind: The implications of a shift to VMT impact metrics

The California Global Warming Solutions Act of 2006 (AB 32) commits California to reduce its greenhouse gas (GHG) emissions to 1990 levels by 2020. The transportation sector is the top GHG emitter in California, contributing roughly 40 percent of all California emissions. Poor fuel efficiency and high vehicle miles traveled (VMT) are primary contributors to transportation sector GHG emissions. Meeting California’s GHG emissions reduction goals requires reductions in both per-mile emissions and vehicle miles traveled. Fuel efficiency has been addressed historically by federal Corporate Average Fuel Economy (CAFE) standards, and California has passed its own legislation regulating GHG emissions from vehicles. Vehicle

Transportation infrastructure demand is driven by a need to replace existing infrastructure and to provide capacity to meet future travel demands. Thus, long-term transportation policy and financial planning benefit from an understanding of future investment needs. The hypothesis that the United States has reached a critical juncture in underlying sociodemographic conditions and travel behavior that will result in more moderate rates of future vehicle miles of travel (VMT) growth is explored. Two simple model formulations for predicting VMT are proposed, and historical trends for establishing inputs for scenario forecasts of future VMT are examined. An understanding of future VMT demand is critical for policy decision making and infrastructure investment planning. The VMT predicting formulas enable National Household Travel Survey information to be used to predict input components in forecasting future VMT. Two VMT predictions are provided and compared with a forecast reported in 2002 Status of the Nation's Highways, Bridges, and Transit: Conditions and Performance. While this study builds a case for slowing VMT growth, it hypothesizes that there may continue to be declining system performance despite slower VMT growth because more of the roadway system is at or near critical congestion levels and hence more susceptible to performance deterioration with modest increases in travel demand. It also suggests that land use pattern effects on travel behavior and person travel time budget growth are the least understood factors and possibly weak links in reaching conclusions about the ultimate pace of VMT growth.

Problem: Congestion pricing and land use planning have been proposed as two promising strategies to reduce the externalities associated with driving, including traffic congestion, air pollution, and greenhouse gas emissions. However, they are often viewed by their proponents as substitutive instead of complementary to each other. Purpose: Using data from a pilot mileage fee program run in Portland, OR, we explored whether congestion pricing and land use planning were mutually supportive in terms of vehicle miles traveled (VMT) reduction. We examined whether effective land use planning could reinforce the benefit of congestion pricing, and whether congestion pricing could strengthen the role of land use planning in encouraging travelers to reduce driving. Methods: VMT data were collected over 10 months from 130 households, which were divided into two groups: those who paid a mileage charge with rates that varied by congestion level (i.e., congestion pricing) and those who paid a mileage charge with a flat structure. Using regression models to compare the two groups, we tested the effect of congestion pricing on VMT reduction across different land use patterns, and the effect of land use on VMT reduction with and without congestion pricing. Results and conclusions: With congestion pricing, the VMT reduction is greater in traditional (dense and mixed-use) neighborhoods than in suburban (single-use, low-density) neighborhoods, probably because of the availability of travel alternatives in the former. Under the same land use pattern, land use attributes explain more variance of household VMT when congestion pricing is implemented, suggesting that this form of mileage fee could make land use planning a more effective mechanism to reduce VMT. In summary, land use planning and congestion pricing appear to be mutually supportive. Takeaway for practice: For policymakers considering mileage pricing, land use planning affects not only the economic viability but also the political feasibility of a pricing scheme. For urban planners, congestion pricing provides both opportunities and challenges to crafting land use policies that will reduce VMT. For example, a pricing zone that overlaps with dense, mixed-use and transit-accessible development, can reinforce the benefits of these development patterns and encourage greater behavioral changes. Research support: This project was supported by the Mineta Transportation Institute, where the authors are research associates.

While voluminous empirical studies have examined the impact of land use on travel behavior, few have relied on longitudinal data and an analytical approach. With data from two activity travel surveys (1997 and 2006) conducted in Austin, Texas, this paper develops a longitudinal multilevel model for estimating the change in the effect of land use on vehicle miles of travel (VMT) over time and the long-range land use effect on VMT reduction. Results suggest that the influences of land use mixture and street density on VMT would vary between 2 years. The effects of VMT reduction on land use policies by raising population and street densities are salient in the short run but insignificant in the long run, whereas those of mixed-use policies are even larger in the long run. These findings validate the importance of longitudinal data and analysis in land use–travel studies and suggest that the short-run elasticity of land use derived from cross-sectional analyses may be inappropriate for assessing the long-run effect of land use–based mobility strategies for reducing VMT.

Adoption of partially automated vehicle technology features and impacts on vehicle miles of travel (VMT)

Outlines new methods for estimating vehicle miles of travel (VMT) under current demographic and land use conditions and projecting VMT under alternative future conditions. Reports on the role that VMT estimates play in evaluating how changing land use patterns and demographics may ultimately affect regional air quality and forest health.

The link between obesity and the built environment. Evidence from an ecological analysis of obesity and vehicle miles of travel in California

Transportation Network Companies (TNCs) play a prominent role in mobility within cities across the globe. However, their activity has impacts on vehicle miles traveled (VMT) and greenhouse gas (GHG) emissions. This study quantifies the change in personal vehicle ownership and total miles driven by TNC drivers in three metropolitan areas: San Francisco, CA; Los Angeles, CA; and Washington, D.C. The data sources for this analysis comprise two surveys, one for TNC passengers (N = 8630) and one for TNC drivers (N = 5034), in addition to data provided by the TNC operators Uber and Lyft. The passenger survey was deployed within the three metropolitan areas in July and August 2016, while the driver survey was deployed from October to November 2016. The TNC operator data corresponded with these time frames and informed the distance driven by vehicles, passenger frequency of use, and fleet level fuel economies. The data from these sources were analyzed to estimate the impact of TNCs on travel behavior, personal vehicle ownership and associated VMT changes, as well as the VMT of TNCs, including app-off driving. These impacts were scaled to the population level and collectively evaluated to determine the net impacts of TNCs on VMT and GHG emissions using fuel economy factors. The results showed that the presence of TNCs led to a net increase of 234 and 242 miles per passenger per year, respectively, in Los Angeles and San Francisco, while yielding a net decrease of 83 miles per passenger per year in Washington, D.C. A sensitivity analysis evaluating net VMT change resulting from vehicle activity and key behavioral impacts revealed the conditions under which TNCs can contribute to transportation sustainability goals.

VMT, energy consumption, and GHG emissions forecasting for passenger transportation

This study aims to evaluate the potential of electric vehicle (EV) carsharing services to address social and environmental disparities in urban transportation through an evaluation of BlueLA, a one-way station-based carsharing service in Los Angeles, California. BlueLA provides a clean and affordable mobility option in underserved communities that face significant air quality burdens and have historically been excluded from environmental benefits. By incorporating BlueLA trip activity data from January 2021 to December 2022 (n = 59,112 trips) and an online user survey implemented in early December 2022 (n = 215 responses), we estimate the impacts of BlueLA on personal vehicle ownership patterns, vehicle miles traveled (VMT), and associated greenhouse gas (GHG) emissions. The results show an overall net reduction in VMT and GHG emissions of 463,845 miles and 656 metric tons, respectively, among the BlueLA user population (3074 registered users). When disaggregating impacts by BlueLA member type, our findings show a net reduction of 234 and 371 metric tons in GHG emissions for Standard (general population) and Community (low-income qualified) members, respectively. Additionally, our socio-demographic analysis highlights clear disparities between these two member groups, with Community members typically having lower incomes (i.e., 74% earning below USD 50,000 annually); lower educational attainment (i.e., 46% with at most an associate’s degree); and larger households (i.e., 23% living in households of four or more) compared to Standard members (i.e., 19% earning below USD 50,000, 24% with at most an associate’s degree, and 9% in households of four or more). Moreover, when comparing the VMT and associated GHG emissions due to BlueLA, we find that the presence of BlueLA reduces VMT and GHG emissions by 34% and 48% respectively, and each BlueLA vehicle replaces 16 personally owned vehicles (shed and postponed purchases). Last, when comparing the emissions produced by the electric fleet of BlueLA to those of a comparable fleet of internal combustion engine vehicles, we find that the use of an EV fleet reduces GHG emissions by 43% in comparison. The BlueLA carsharing service has led to notable net reductions in VMT and thus GHG emissions, with a major share of these reductions observed among Community members.

The Carnegie Endowment for International Peace (CEIP), through its Leadership Initiative for Transportation Solvency, in 2011 released Road to Recovery: Transforming America's Transportation, a report that proposed a new revenue mechanism to fund a reformed transportation program fully. The report recommends that Congress couple a per barrel oil fee with a variable, countercyclical gas tax. This paper discusses the dynamic impacts of CEIP's revenue policy on household travel behavior, revenue generation for the federal trust fund, energy consumption, equity, and greenhouse gas (GHG) emissions and air pollution at the national level from 2008 to 2010. The analysis developed econometric models: a multiple vehicle miles traveled (VMT) regression model and a discrete vehicle ownership model. Model results showed that the CEIP revenue proposal could fill the revenue shortfall regardless of the world oil price. During the historic study period of 2008 to 2010, the CEIP policy would have collected up to more than double the federal revenue. At the same time, households would have increased their VMT by as much as 1.8% when oil prices peaked, and reduced their VMT by up to 8.6% when the crude oil price dropped to the lowest point. It is estimated that, without any investments or revenue recycling, lower-income households would have experienced a 0.45% to 0.5% reduction in consumer surplus changes measured as a percentage of income and higher-income households would have experienced a 0.06% to 0.1% reduction. Finally, it is estimated that the CEIP policy would have reduced air pollution and GHG emissions by an average 4% to 4.35% for different pollutant types.