Institute of Transportation Studies

We investigate the impacts of a combination of incentives on the purchase decisions of electric vehicle (EV) buyers in California from 2010 through 2017. We employ a comprehensive survey on over 14,000 purchasers of EVs in California. The survey covers a range of purchase intentions, general demographics, and the importance of various incentives. Our results indicate that the most important incentives for plug-in electric vehicle (PEV) owners are the federal tax credit, the state rebate, and HOV lane access. In addition, the importance of the incentives and their associated effect on purchase behaviour has been changing over time: respondents are more likely to change their decisions and to not buy a vehicle at all as time passes and the technology moves away from early adopters.

Highlights

As part of the state’s overall strategy to reduce greenhouse gas (GHG) emissions, Oregon’s Clean Fuels Program (CFP) aims to reduce transportation sector emissions by incentivizing innovation, technological development, and deployment of low-emission alternative fuels and vehicles. It isdesigned as a performance standard, rather than a prescriptive approach to emissions reduction. It sets an annual declining target in fuel carbon intensity (CI) with a goal of 10% reduction by 2025 relative to 2015 levels.

The CFP has been in effect for three years, with relatively small but growing CI reduction targets of 0.25% in 2016, 0.5% in 2017, and 1.0% in 2018, with a 2019 CI target of 1.5%. The CFP had 163 registered parties and 283 transportation fuel pathways available for use as of the end of 2018.

From 2016 through 2018 Q3, total emissions reduction requirements were 2.4 million metric tons (MMT) CO2e and reported emissions reductions were 2.0 MMT CO2e, representing overcompliance of over 421,000 tons CO2e and creating a systemwide “bank” of program credits(each representing 1 MT CO2e) that can be used to meet future targets. Data for 2018 lacked residential electricity credits at the time of writing.

The program generated excess credits relative to deficits in every quarter through 2017. With 2018 electricity credits not yet reported, 2018 deficits through Q3 exceeded credits by under 1,700, well below the 30,000 credits generated by residential electricity in 2017 Q1–Q3, and theabout 29,000 credits for the same category that would be generated under 2018 standards given the same energy.

Aggregate alternative fuel energy consumption remained approximately stable over the program period—the program’s operation thus far. Ethanol contributed the largest share of alternative fuel and remained between 10% and 11% by volume of blended gasoline, at or just above the“blendwall” of 10% blends, through the period. Between 2016 and 2017, the only two years of complete data, transport energy from fossil natural gas, biogas, propane, and non-residential electricity each grew by over 50%, and from biodiesel grew by over 7%.

The average annual CI rating for most reported alternative fuels declined between 2016 and 2018 through Q3, including the biggest volume contributors, ethanol (just under 1.5% decline) and biodiesel (just over 17% decline).

Prices of CFP compliance credits (each representing 1 MT CO2e) remained in the $40–$50 range through 2016 and 2017. The yearly average increased to $84 in 2018 as volumes traded also rose. Data through March 2019 indicate an average price around $145.

Oregon’s CFP shares some design similarities with California’s Low Carbon Fuel Standard(LCFS), but also has some differences in terms of program targets and baseline fuel blends, treatment of indirect land use change, residential electricity for electric-vehicle (EV) charging, and other credit generation and credit market elements. The programs, along with a similar policyin British Columbia, are part of the Pacific Coast Collaborative commitment to low carbon fuels and economies among these jurisdictions. Washington state is currently considering a similar clean fuel standard as part of its legislative process.

The research project presented in this report evaluates the effects that the addition of aramid fibers has on the mechanical properties of a dense-graded mix frequently used in California, a Superpave mix with 19 mm (3/4 in.) nominal maximum aggregate size, 15 percent reclaimed asphalt pavement (RAP) content, and PG 64-10 binder. A fiber-reinforced asphalt concrete (FRAC) was prepared by adding aramid fibers at a rate of 0.013 percent of total mix weight. The mechanical properties of the two mixes, original and FRAC, were determined in the laboratory. Based on laboratory testing, adding the fibers improved fatigue resistance of the original mix at high strain levels considerably. It also improved rutting resistance while only changing the stiffness a little. The added fibers did not negatively impact the compactability of the mix nor did it seem to change the mix volumetrics. The laboratory testing results indicate that adding aramid fibers would be of greatest value where asphalt is subjected to high strain levels, such as in overlays of jointed concrete pavements or in pavements with considerable cracking. This study did not consider any occupational health risks, environmental risks or cost considerations, effects on constructability (particularly compaction) in the field, or what effects added fibers might have on the ability to recycle fiber-reinforced asphalt pavement.

The survey project described here is intended to be the beginning of a multi-year project on the effectiveness of various activities in growing consumer interest in purchasing BEVs in the Sacramento region.

This survey in Sacramento shows that engagement in PEVs is moderate, based on the following results: 50% of respondents had seen some PEV-related advertising, mostly on television or in print media; 47% were aware of the California Clean Vehicle Rebate, and 46% aware of the federal tax credit; 40% could correctly name a PHEV, and 50% a BEV; 25% had sought out information on PEVs, mostly through the internet or speaking to car salespeople, friends, or family. Compared to respondents to a 2014 state-wide survey, a higher percentage of respondents to this 2018 Sacramento survey had seen charging stations, and a similar percentage, 3.3%, had actively shopped for a BEV. Ordinal logistic regression modelling indicated that the following factors were associated with having considered purchasing a BEV: being enthusiastic about PEVs, knowing someone by name who owns a PEV, having sought out information on PEVs, knowing how to refuel a PEV, and being familiar with the vehicles. Considering a BEV purchase was not associated with: having seen advertising, being aware of ride-and-drive events, having been in a PEV, having seen chargers, awareness of incentives, or the density of PEVs or charging stations near the respondent’s home.

Results suggest that respondents who are interested in BEVs are a self-selecting group whose interest is not the result of promotional activities. Existing efforts to engage the general population not yet had a significant impact on respondents thinking about purchasing a BEV. Future follow-up surveys will be able to track changes in respondent awareness, the impact of various advertising and awareness campaigns, and growing consumer engagement in PEVs over time.

We currently know little about what to expect regarding ride-pooling in shared automated vehicles (SAVs). Who will be willing to share rides, with whom, and under what conditions? This report details the efforts and results funded by two seed grants that converged on these questions. A broad-based literature review and review of automated vehicle (AV designs) leads to the articulation of potential risks and benefits of the pooled SAV experience and potential design solutions and supports, respectively. Risks could be related to compromised personal space, security, control, and convenience. Design features that might mitigate these risks include large windows to afford a high degree of visibility into and out of the vehicle, spacious seating and legroom (relative to larger shared vehicles like buses, trains, and planes), access to a remote human administrator who can observe inside the vehicle at all times, easy means to program private stops that are nearby one’s ultimate origins and destinations (to maintain privacy), and options for large groups or associations to “own” a particular vehicle (e.g., a female only SAV). Benefits of pooled SAVs could be related to restoration and social capital. Design features that could support these benefits include themed interiors; quizzes, games and ambient entertainment; augmented reality windshields; flexible seating allowing riders to face each other; accommodations for food and drink; ensuring broad access; and making SAVs a canvas for local art. The reports ends with a proposed research agenda highlighting the importance of qualitative engagement with consumers to understand the issues related to: switching to pooled SAVs from various dominant travel modes (e.g., private cars, ride-hailing, public transit); leveraging analogous modes (e.g., pooled ride-hailing) to study the potential of pooled SAVs; and conducting experiments to understand the influence of various features of the pooled SAV experience that will impact consumer adoption. This report can inform SAV designers, policy-makers, private transit service providers, and other stakeholders about behavioral and design factors that will impact uptake of pooled SAVs.

In the last decade, advances in information and communication technologies and the introduction of the shared economy engendered new forms of transportation options and, in particular, shared mobility. Shared mobility services such as carsharing (e.g., Zipcar and Car2go), dynamic ridesharing (e.g., Carma), ridehailing (e.g., Uber and Lyft), and bike/scooter sharing (e.g., CitiBike, Jump Bike, Bird, and Lime) have gained growing popularity especially among subgroups in the population including college-educated or urban-oriented young adults (e.g., millennials). These emerging transportation services have evolved at an unprecedented pace, and new business models and smartphone applications are frequently introduced to the market. However, their fast-changing nature and lack of relevant data have placed difficulties on research projects that aim to gain a better understanding of the adoption/use patterns of such emerging services, not to mention their impacts on various components of travel behavior and transportation policy and planning, and their related environmental impacts.

This report builds on an on-going research effort that investigates emerging mobility patterns and the adoption of new mobility services. In this report, the authors focus on the environmental impacts of various modality styles and the frequency of ridehailing use among a sample of millennials (i.e., born from 1981 to 1997) and members of the preceding Generation X (i.e., born from 1965 to 1980). The total sample for the analysis included in this report includes 1,785 individuals who participated in a survey administered in Fall 2015 in California. In this study, the researchers focus on the vehicle miles traveled, the energy consumption and greenhouse gas (GHG) emissions for transportation purposes of various groups of travelers. They identify four latent classes in the sample based on the respondents’ reported use of various travel modes: drivers, active travelers, transit riders, and car passengers. They further divide each latent class into three groups based on their reported frequency of ridehailing use: non-users, occasional users (who use ridehailing less than once a month), and regular users (who use it at least once a month). The energy consumption and GHG emissions associated with driving a personal vehicle and using ridehailing services are computed for the individuals in each of these groups (12 subgroups), and the authors discuss sociodemographics and economic characteristics, and travel-related and residential choices, of the individuals in each subgroup.

View the NCST Project Webpage

Individual travel options are quickly shifting due to changes in sociodemographics, individual lifestyles, the increased availability of modern communication devices (smartphones, in particular) and the adoption of emerging transportation technologies and shared-mobility services. These changes are transforming travel-related decision-making in the population at large, and especially among specific groups such as young adults (e.g., “millennials”) and the residents of urban areas.

This panel study improves the understanding of the impacts of emerging technologies and transportation trends through the application of a unique longitudinal approach. The authors build on the research efforts that led to the collection of the 2015 California Millennials Dataset and complement them with a second wave of data collection carried out during 2018, generating a longitudinal study of emerging transportation trends with a rotating panel structure. The use of longitudinal data allows researchers to better assess the impacts of lifecycle, periods and generational effects on travel-related choices, and analyze components of travel behavior such as the use of shared mobility services among various segments of the population and its impact on vehicle ownership over time. Further, it helps researchers evaluate causal relationships between variables, thus supporting the development of better-informed policies to promote transportation sustainability.

View the NCST Project Webpage

A multitude of goals have been stated for complete streets including non-motorized travel safety, reduced costs and environmental burdens, and creation of more livable communities, or in other words, the creation of livable, sustainable and economically vibrant communities. A number of performance measures have been proposed to address these goals. Environmental life cycle assessment (LCA) quantifies the energy, resource use, and emissions to air, water and land for a product or a system using a systems approach. One gap that has been identified in current LCA impact indicators is lack of socio-economic indicators to complement the existing environmental indicators. To address the gaps in performance metrics, this project developed a framework for LCA of complete streets projects, including the development of socio-economic impact indicators that also consider equity. The environmental impacts of complete streets were evaluated using LCA information for a range of complete street typologies. A parametric sensitivity analysis approach was performed to evaluate the impacts of different levels of mode choice and trip change. Another critical question addressed was what are different social goals (economic, health, safety, etc.) that should be considered and how to consider equity in performance metrics for social goals. This project lays the foundation for the creation of guidelines for social and environmental LCAs for complete streets.

View the NCST Project Webpage

In much in the same way that the automobile disrupted horse and cart transportation in the 20th century, automated vehicles hold the potential to disrupt our current system of transportation in the 21st century. Experts predict that vehicles could be fully automated by as early as 2025 or as late as 2035. Methods are needed to help the public and private sector understand automated vehicle technologies and their system-level effects. First, we explore the effects of automated vehicles using the San Francisco Bay Area Metropolitan Transportation Commission’s activity-based travel demand model (MTC-ABM). The simulation is unique in that it articulates the size and direction of change on travel for a wide range of automated vehicles scenarios. Second, we simulate the effects of the introduction of an automated taxi service on conventional personal vehicle and transit travel in the San Francisco Bay Area region and use new research on the costs of automated vehicles to represent plausible per mile automated taxi fares. We use an integrated model for the San Francisco Bay Area that includes the MTC-ABM combined with the agent-based MATSim model customized for the region. This model set uses baseline travel demand data from the region’s official activity-based travel model and dynamically assigns vehicles on road and transit networks by the time of day. Third, we use the MTC-ABM and the MATSim dynamic assignment model to simulate different “first” mile transit access services, including ride-hailing (Uber and Lyft) and ridesharing (Uber Pool/Lyft Line and Via) with and without automated vehicles. The results provide insight into the relative benefits of each service and automated vehicle technology and the potential market for these services.

View the NCST Project Webpage

Transportation is a major emitter of greenhouse gas (GHG) emissions in the United States accounting for 27% of the country’s emissions, second only to the electricity sector. As a result, reducing GHG emissions are essential for mitigating some of the most damaging potential impacts associated with climate change and because of the importance and relative size of the transportation sector, it would need to contribute a significant amount of emissions reduction.

This report describes the development and use of an U.S. energy system optimization model (US-TIMES) in order to analyze the reductions in GHG emissions that can come about through policy targets.  These policy targets induce technology investments and operation in order to satisfy the demand for energy services and environmental policy constraints (notably GHG emission targets).

The model development focused on two key areas within the transportation sector, light-duty vehicles and heavy-duty vehicles.  In the light-duty space, we incorporated consumer choice elements into the energy system optimization framework through increasing consumer heterogeneity and adding non-monetary decision factors such as risk and fueling inconvenience.  For heavy-duty vehicles, we adopt a segmentation approach and update vehicle cost and performance assumptions from our recent work. The model is used to project scenarios for low carbon futures from a reference scenario all the way to an 80% GHG reduction target.

View the NCST Project Webpage