Ride-Hailing Holds Promise for Facilitating More Transit Use in the San Francisco Bay Area

Increasing transit use has many benefits, including reducing traffic congestion and greenhouse gas (GHG) emissions. However, riders need to be able to get to a station in order to use transit. Walking is an option only for those within a limited radius of a station. Driving to a station may be feasible for some, but providing sufficient parking can be expensive and land intensive. The rise of ride-hailing companies such as Uber and Lyft presents a new opportunity for bridging the “first-mile” gap to high quality transit. Transit agencies are beginning to launch pilot projects to test public-private partnerships with ride-hailing companies to increase access to transit.This policy brief summarizes findings from researchers at UC Davis who used existing modeling tools and data to understand the potential market demand for a first-mile transit access service in the San Francisco Bay Area. They modeled the likelihood of commuters who drive alone to switch to using ride-hailing and the Bay Area Rapid Transit (BART) rail system to get to work based on travel time, cost, and distance to a BART station. They explored the magnitude of change in overall travel time and cost for travelers who switch from driving alone to using ride-hailing and BART, as well as potential changes to vehicle miles traveled (VMT) and GHG emissions at both the regional and station level.View the NCST Project Webpag

Synergistic Interactions of Dynamic Ridesharing and Battery Electric Vehicles Land Use, Transit, and Auto Pricing Policies

It is widely recognized that new vehicle and fuel technology is necessary, but not sufficient, to meet deep greenhouse gas (GHG) reductions goals for both the U.S. and the state of California. Demand management strategies (such as land use, transit, and auto pricing) are also needed to reduce passenger vehicle miles traveled (VMT) and related GHG emissions. In this study, the authors explore how demand management strategies may be combined with new vehicle technology (battery electric vehicles or BEVs) and services (dynamic ridesharing) to enhance VMT and GHG reductions. Owning a BEV or using a dynamic ridesharing service may be more feasible when distances to destinations are made shorter and alternative modes of travel are provided by demand management strategies. To examine potential markets, we use the San Francisco Bay Area activity based travel demand model to simulate business-as-usual, transit oriented development, and auto pricing policies with and without high, medium, and low dynamic ridesharing participation rates and BEV daily driving distance ranges. The results of this study suggest that dynamic ridesharing has the potential to significantly reduce VMT and related GHG emissions, which may be greater than land use and transit policies typically included in Sustainable Community Strategies (under California Senate Bill 375), if travelers are willing pay with both time and money to use the dynamic ridesharing system. However, in general, large synergistic effects between ridesharing and transit oriented development or auto pricing policies were not found in this study. The results of the BEV simulations suggest that TODs may increase the market for BEVs by less than 1% in the Bay Area and that auto pricing policies may increase the market by as much as 7%. However, it is possible that larger changes are possible over time in faster growing regions where development is currently at low density levels (for example, the Central Valley in California). The VMT Fee scenarios show larger increases in the potential market for BEV (as much as 7%). Future research should explore the factors associated with higher dynamic ridesharing and BEV use including individual attributes, characteristics of tours and trips, and time and cost benefits. In addition, the travel effects of dynamic ridesharing systems should be simulated explicitly, including auto ownership, mode choice, destination, and extra VMT to pick up a passenger

Travel Behavior Impacts of Transportation Demand Management Policies: May is Bike Month in Sacramento, California

UC-ITS-2018-49Active modes of transportation like bicycling and walking are extremely beneficial to society, including helping to reduce the amount of travel people may make by car (i.e., vehicle miles travelled) and in turn reducing congestion and transportation-related greenhouse gas emissions and air pollutants. Bicycling and walking also have direct and positive health impacts. Several steps have been taken to promote active transportation in cities and regions, including awareness campaigns, transportation demand management policies, building new bicycling infrastructure, and the launch of bikesharing programs. However, it is often unclear how much impact a specific strategy can have on actual rates of bicycling and walking in a community or region. UC Davis assisted the Sacramento Council of Governments (SACOG) in evaluating the impact of the agency\u2019s \u201cMay is Bike Month\u201d campaign

Panel Study of Emerging Transportation Technologies and Trends in California: Phase 2 Data Collection

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., \u201cmillennials\u201d) 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. We 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

Future Connected and Automated Vehicle Adoption Will Likely Increase Car Dependence and Reduce Transit Use without Policy Intervention [Policy Brief]

Researchers at the University of California, Davis investigated the range of potential impacts that rapid adoption of CAVs in California might have on vehicle miles traveled and emissions. The researchers estimated the vehicle miles traveled and emissions of each scenario using a statewide travel demand model, emissions factors from California agencies, and assumptions derived from the scientific literature and expert input. This policy brief summarizes the findings from that research and provides policy implications

What Affects U.S. Passenger Travel? Current Trends and Future Perspectives

65A0527 TO 010The United States is going through an era of unprecedented transformation. Sociodemographic changes, major innovations in information technology, the reorganization of economic activities, and substantial shifts in the urban form of cities all contribute to changing the way Americans live, work, and travel. During the past ten years, transportation demand in the United States has also gone through significant modifications. The use of private vehicles has gone through a period of apparent stagnation. Starting in the mid-2000s, the average per-capita vehicle miles traveled (VMT) have declined, at least temporarily (until 2013), after a long period of steady growth in the previous decades. In addition, an increased portion of Americans live without a car. While the total amount of trips in the country continues to rise, this has not translated into increased car use, and the use of alternative modes (including public transportation and active means of travel) is increasing, even if it still accounts for a rather low portion of mode share. Passenger travel in the United States at the beginning of the 21st century is increasingly multimodal, and (slightly) less reliant on the use of private cars. Travelers are changing their behaviors in response to new alternatives available to them, changes in the characteristics of the old alternatives, and changes in the way they evaluate and value these characteristics. A complex combination of factors is behind the observed trends. The economic crisis from 2007-2009 certainly contributed to reducing total VMT in the country. However, it is not the main cause of the observed changes in travel behavior, and other factors seem to play an important role. In particular, several studies have demonstrated how the observed reduction in car travel actually predates the economic crisis by at least a few years

Exploring the Relationships Among Travel Multimodality, Driving Behavior, Use of Ridehailing and Energy Consumption

This report builds on an on-going research effort that investigates emerging mobility patterns and the adoption of new mobility services. In this report, we 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, we focus on the vehicle miles traveled, the energy consumption and greenhouse gas (GHG) emissions for transportation purposes of various groups of travelers. We identify four latent classes in the sample based on the respondents\u2019 reported use of various travel modes: drivers, active travelers, transit riders, and car passengers. We 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 we discuss sociodemographics and economic characteristics, and travel-related and residential choices, of the individuals in each subgroup

What Affects Millennials\u2019 Mobility? Part I: Investigating the Environmental Concerns, Lifestyles, Mobility-Related Attitudes and Adoption of Technology of Young Adults in California

65A0527 TO 011Recent research has highlighted significant modifications in travel demand, suggesting a \u201cVMT Peak\u201d, and a peak in car ownership among young adults in California and the rest of the United States. In order to investigate this topic, and the motivations behind these trends, this study will undertake a detailed investigation of travel behavior and the propensity to purchase a car among young adults (aged 18-30) in California. Through the assistance of a commercial vendor, the authors will develop a representative sample of the population of young adults in California, and administer an online survey developed as part of the project. The research will explore the impact of a range of factors, including personal attitudes and preferences (e.g. about travel, the adoption of technology, the adoption of alternative-fuel vehicles, social, economic and environmental issues), lifestyles, the urban form, the individual\u2019s living arrangements, the influence of peers and online social networks. The study will build on other studies and provide critical insights into the motivations affecting young persons\u2019 travel behavior and car-ownership aspirations, and will allow researchers and policy-makers to better understand likely future trends in travel demand and the potential responses to policies designed to increase transportation sustainability