Automated vehicles, if shared, have the potential to blur the lines between public and private transportation services. This chapter reviews possible future shared automated vehicle (SAV) business models and their potential impacts on travel behavior. By examining the impacts of non-automated shared mobility services like carsharing and ridesourcing, we foster a better understanding of how current shared mobility services affect user behavior. This serves as a starting point to explore the potential impact of SAV services. Several key studies covering the topic are discussed. Although the future of SAVs is uncertain, this chapter begins the dialogue around SAV business models that may develop, which are informed by current shared mobility services.

This white paper examines the social equity impacts of various congestion management strategies. The paper includes a comprehensive list of 30 congestion management strategies and a discussion of equity implications related to each strategy. The authors analyze existing literature and incorporate findings from 12 expert interviews from academic, non-governmental organization (NGO), public, and private sector respondents to strengthen results and fill gaps in understanding. The literature review applies the Spatial – Temporal – Economic – Physiological – Social (STEPS) Equity Framework (Shaheen et al., 2017) to identify impacts and classify whether social equity barriers are reduced, exacerbated, or both by a particular congestion mitigation measure. The congestion management strategies discussed are grouped into six main categories, including: 1) pricing, 2) parking and curb policies, 3) operational strategies, 4) infrastructure changes, 5) transportation services and strategies, and 6) conventional taxation. The findings show that the social equity impacts of certain congestion management strategies are not well understood, at present, and further empirical research is needed. Congestion mitigation measures have the potential to affect travel costs, commute times, housing, and accessibility in ways that are distinctly positive or negative for different populations. For these reasons, social equity implications of congestion management strategies should be understood and mitigated for in planning and implementation of these strategies.

To better understand the equity implications of a variety of congestion management strategies, researchers at the Transportation Sustainability Research Center (TSRC) at University of California, Berkeley analyzed existing literature on congestion management strategies and findings from 12 expert interviews. The literature review applies the Spatial – Temporal – Economic – Physiological – Social (STEPS) Equity Framework1 to identify impacts and classify whether social equity barriers are reduced, exacerbated, or both by a particular strategy. The congestion management strategies of interest were categorized into six broader categories: 1) pricing, 2) parking and curb policies, 3) operational strategies, 4) infrastructure changes, 5) transportation services and strategies, and 6) conventional taxation.

Transportation is arguably experiencing its most transformative revolution since the introduction of the automobile. Concerns over climate change and equity are converging with dramatic technological advances. Although these changes – including shared mobility and automation – are rapidly altering the mobility landscape, predictions about the future of transportation are complex, nuanced, and widely debated. California is required by law to renew the California Transportation Plan (CTP), updating its models and policy considerations to reflect industry changes every five years. This document is envisioned as a reference for modelers and decision makers. We aggregate current information and research on the state of key trends and emerging technologies/services, documented impacts on California’s transportation ecosystem, and future growth projections (as appropriate). During 2017, we reviewed an expanded list of 20 topics by referencing state agency publications, peer-reviewed journal articles, and forecast reports from consulting firms and think tanks. We followed transportation newsletters and media sources to track industry developments, and interviewed six experts to explore their opinions on the future of transportation. We consulted an advisory committee of over 50 representatives from local and state transportation agencies, who provided input throughout the project’s evolution. We also obtained feedback on our draft report from a panel of U.S. experts.

This chapter examines the characteristics and practices of ridesharing users in France. In May 2013, the authors surveyed members of BlaBlaCar, the largest online and app-based carpooling service in France, to analyze the sociodemographic characteristics and usage patterns of the respondents. The survey results identify correlations between socio-demographic characteristics and usage elements. Notably, users with a lower income level are more inclined to be passengers, while higher income users employ carpooling mainly as drivers. Students are shown to be more frequent users as well. These findings indicate some equity balancing effects, which may be unique to this shared mobility mode.

The study found that roundtrip carsharing in NYC mostly serves as a substitute for car rental, other personal vehicle modes, and personal vehicle ownership. The analysis showed that the broader pilot program had a modest impact on user behavior through carsharing (i.e., reduced vehicle ownership, reduced VMT, and mode shift). It also found that the pilot program likely expanded the membership base of carsharing to demographic cohorts that are traditionally underrepresented in carsharing populations (i.e., increased participation by lower education levels, lower household incomes, minority demographics). The study also examined vehicle ownership impacts and changes in vehicle miles traveled (VMT) and greenhouse gas (GHG) emissions. Analysis of survey and activity data indicated that 7% of NYC carsharing members avoided a car purchase, and 0.61% of members got rid of a car they already owned due to carsharing. Across the membership base, VMT was reduced by 7% and GHG emissions were reduced by 6%. These findings showed that carsharing reduced VMT and delivered associated environmental benefits within NYC, and more broadly had a substantive impact on travel behavior among members in form of mode shift away from personal automotive modes.

Transportation Network Companies (TNCs, also known as ridehailing and ridesourcing) have expanded across California over the past decade and changed the way people travel. Using a smartphone, travelers can quickly summon a vehicle from almost anywhere and know what the estimated wait time, travel time, and cost will be before stepping into the vehicle. While TNCs are clearly addressing an unmet need for travelers, their growing popularity has raised a number of policy questions, including if TNCs are shifting people away from public transit and other travel modes (e.g., carshare, walking, biking).

The Mobility on Demand (MOD) Sandbox Demonstration Program provides a venue through which integrated MOD concepts and strategies, supported through local partnerships, are demonstrated in real-world settings. For the 11 MOD Sandbox Demonstration projects, an independent evaluation was conducted that includes an analysis of project impacts from performance measures provided by the project partners and an assessment of the business models used. This document presents the results from the independent evaluation of the Dallas Area Rapid Transit (DART) First and Last Mile Solution MOD Sandbox Demonstration project. Evaluated were hypotheses that explored project impacts on travel behavior, user experiences, first and last mile to public transit accessibility, service quality for passengers with disabilities, and costs. The project improved first and last mile connectivity to DART transit, increased satisfaction among DART transit users, enhanced service for passengers with disabilities, and increased the geographic scope of DART transit service in the Plano area. In addition, wait and travel times for passengers with and without disabilities reflected similar distributions. The subsidy per rider of GoLink services was lower than the low-ridership fixed-route transit services that it replaced in Plano, but it was not lower than the subsidy for DART fixed-route transit in the overall Dallas region. DART project team members were interviewed to better understand challenges, barriers, successes, and broader lessons learned from the project, representing agency personnel from the offices of Innovation, Service Planning, Scheduling, Paratransit Operations, and Marketing. Lessons learned revealed the importance of having pre-planned, ready-to-go projects with committed partners, flexible contracting terms, metrics for adjusting spatial and temporal service coverage (including terminating service if appropriate), vehicle right-sizing, and understanding customer needs.

Transportation Network Companies (TNCs) like Lyft, Uber, and their global counterparts have expanded around the world over the past decade and have changed the way that people travel around cities and regions. The individual mobility benefits provided by TNCs have been clear. Passengers can summon a vehicle quickly via smartphone from almost anywhere to take them almost anywhere, with advance communication on estimated wait time, travel time, and cost. TNCs may also provide users with added mobility benefits, especially for those living in areas where public transit service is infrequent or non-existent. However, the growing popularity of TNCs has forced important questions about their impacts on the overall transportation network. While past research has focused on many different aspects of TNC impacts, including their effects on travel behavior, modal shift, congestion, and other topics, there are still many important questions. This report advances the understanding of TNC effects on vehicle miles traveled (VMT), greenhouse gas (GHG) emissions, and personal vehicle ownership. The research also explores key questions regarding the impact of pooled TNC services, Lyft Shared rides and uberPOOL, and further investigates how TNCs alter the use of other transportation modes, including public transit.