Read “Mobility on Demand (MOD) and Mobility as a Service (MaaS): Similarities, Differences, and Potential Implications for Transportation in the Developing World ” by Susan Shaheen and Adam Cohen

Innovative and emerging transportation services, such as shared mobility, MOD, and MaaS, are expanding across the developing world. MOD emphasizes the commodification of passenger mobility and goods delivery and transportation systems management, whereas MaaS primarily focuses on passenger mobility aggregation and subscription services. The public
sector can support and leverage MOD and MaaS through a variety of service, information, fare integration, and data sharing partnerships. In particular, the growth of “super” apps in Africa and Asia are offering consumers all-in-one mobile platforms for a variety of transportation and shopping options, mobile wallets, and other services that, in some cases, offer deeper levels of integration and are more advanced than comparable platforms in Europe and North America. While research on “super” apps is
limited, anecdotal evidence suggests that by bundling a variety of consumer services together, these apps have the potential to enhance traveler convenience, multimodal trip planning, and access to goods and services.

Read “Strategies to Overcome Transportation Barriers for Rent Burdened Oakland Residents” by Alexandra Pan and Susan Shaheen

Shared mobility is gaining traction in the transportation community as a potentially more environmentally friendly alternative to automobile travel and complement to public transit. However, adoption and use of shared mobility by low-income individuals lags behind other demographic groups. Additional research is needed to better understand the transportation needs of low-income travelers and how public agencies, community-based organizations, and shared mobility operators can work together to best serve those needs.

This research fills gaps in understanding the potential policy strategies that could be effective at increasing the access, awareness, and use of shared mobility by low-income individuals. We employ Oakland, California as our primary study site (see Figure 1 and Table 1 for more detail). In this report, we present our findings on barriers to shared mobility from a review of existing shared mobility social equity initiatives, expert interviews (n=13) and focus groups with rent burdened residents of East Oakland (n=24). We further investigate barriers and implications for transportation use in an online survey (n=177), as well as longitudinal panel of phone and video interviews (n=31) with rent burdened Oakland residents. Rent burden refers to the percentage of income spent on rent and can more widely capture the population of Oakland residents who are struggling to keep up with rising housing costs.

Read “Bridging the Income and Digital Divide with Shared Automated Electric Vehicles” by Jessica Lazarus, Gordon Bauer, Jeffery Greenblatt, and Susan Sheen 

This research investigates strategies to improve the mobility of low-income travelers by incentivizing the use of electric SAVs (SAEVs) and public transit. We employ two agent-based simulation engines, an activity-based travel demand model of the San Francisco Bay Area, and vehicle movement data from the San Francisco Bay Area and the Los Angeles Basin to model emergent travel behavior of commute trips in response to subsidies for TNCs and public transit. Sensitivity analysis was conducted to assess the impacts of different subsidy scenarios on mode choices, TNC pooling and match rates, vehicle occupancies, vehicle miles traveled (VMT), and TNC revenues. The scenarios varied in the determination of which travel modes and income levels were eligible to receive a subsidy of $1.25, $2.50, or $5.00 per ride. Four different mode-specific subsidies were investigated, including subsidies for 1) all TNC rides, 2) pooled TNC rides only, 3) all public transit rides, and 4) TNC rides to/from public transit only. Each of the four modespecific subsidies were applied in scenarios which subsidized travelers of all income levels, as well as scenarios that only subsidized low-income travelers (earning less than $50,000 annual household income). Simulations estimating wait times for TNC trips in both the San Francisco Bay Area and Los Angeles regions also revealed that wait times are distributed approximately equally across low- and high-income trip requests.

Read “To Pool or Not to Pool? Understanding the Time and Price Tradeoffs of OnDemand Ride Users – Opportunities, Challenges, and Social Equity Considerations for Policies to Promote Shared-Ride Services” by Susan Shaheen, Jessica Lazarus, Juan Caicedo, and Alexandre Bayen

On-demand mobility services including transportation network companies (also known as ridesourcing and ridehailing) like Lyft and Uber are changing the way that people travel by providing dynamic mobility that can supplement public transit and personal-vehicle use. However, TNC services have been found to contribute to increasing vehicle mileage, traffic congestion, and greenhouse gas emissions. Pooling rides ⎯ sharing a vehicle by multiple passengers to complete journeys of similar origin and destination ⎯ can increase the average vehicle occupancy of TNC trips and thus mitigate some of the negative impacts. Several mobility companies have launched app-based pooling services in recent years including app-based carpooling services (e.g., Waze Carpool, Scoop) that match drivers with riders; pooled on-demand ride services (e.g., Uber Pool and Lyft Shared rides) that match multiple TNC users; and microtransit services (e.g., Bridj, Chariot, Via) that offer on-demand, flexibly routed service, typically in larger vehicles such as vans or shuttles. However, information on the potential impacts of these options is so far limited. This research employs a general population stated preference survey of four California metropolitan regions (Los Angeles, Sacramento, San Diego, and the San Francisco Bay Area) in Fall 2018 to examine the opportunities and challenges for drastically expanding the market for pooling, accounting for differences in emergent travel behavior and preferences across the four metropolitan regions surveyed. The travel profiles, TNC use patterns, and attitudes and perceptions of TNCs and pooling are analyzed across key socio-demographic attributes to enrich behavioral understanding of marginalized and price sensitive users of on-demand ride services. This research further develops a discrete choice model to identify significant factors influencing a TNC user’s choice to pool or not to pool, as well as estimating a traveler’s value of time (VOT) across different portions of a TNC trip. This research provides key insights and social equity considerations for policies that could be employed to reduce vehicle miles traveled and emissions from passenger road transportation by incentivizing the use of pooled on-demand ride services and public transit.

Read “Public Transit and Shared Mobility COVID-19 Recovery: Policy Recommendations and Research Needs” by Susan Shaheen and Stephen Wong.

While the COVID-19 crisis has devastated many public transit and shared mobility services, it has also exposed underlying issues in how these services are provided to society. As ridership drops and revenues decline, many public and private providers may respond by cutting service or reducing vehicle maintenance to save costs. As a result, those who depend on public transit and shared mobility services, particularly those without access to private automobiles, will experience further loss of their mobility. These transportation shifts will be further influenced by changing work-from-home policies (e.g., telework). While uncertainty remains, work-from-home will likely alter public transit and shared mobility needs and patterns, necessitating different services, operation plans, and business structures.

Read “Synthesis of State-Level Planning and Strategic Actions on Automated Vehicles: Lessons and Policy Guidance for California” by Stephen Wong and Susan Shaheen.

This synthesis provides a summary and comparative analysis of actions states across the United States are taking inresponse to automated vehicles (AVs). The research focuses on state-level stakeholder forums (e.g., task forces, committees) and state-level strategic actions (e.g., studies, initiatives, programs) initiated by a state legislature, agovernor, or a state agency. The analysis found that AV stakeholder forums and strategic actions address a diverse set offocus areas, but they pay minimal attention to the implications of AVs on the environment, public health, social equity, land use, public transit, goods movement, and emergency response. Also, forums and strategic actions commonly include members from state transportation departments, the legislature, and academia; however, representatives from industry and non-governmental organizations (NGOs) are included less often. Academia and researchers participate in themajority of AV forums and actions, either in an advisory capacity (i.e., sharing expertise and experience) and/or through conducting research. Based on this analysis, the synthesis concludes with a recommendation for California to form a state-level working group representing leaders from the public sector, industry, NGOs, and academia to advise the Governor and the Legislature on AV policy across a range of focus areas.

Read “Mobility on Demand Planning and Implementation: Current Practices, Innovations, and Emerging Mobility Futures” by Susan Shaneen, Adam Cohen, Jacquelyn Broader, Richard Davis, Les Brown, Radha Neelakantan, and Deepak Gopalakrishna.

This report provides Mobility on Demand (MOD) planning and implementation practices and tools to support communities. The report discusses different stakeholders in the MOD ecosystem and the role of partnerships in filling spatial, temporal, and other service gaps. Additionally, the report discusses how MOD can be integrated into transportation planning and modeling. The report also discusses shared mobility implementation considerations, such as rights-of-way management, multimodal integration, data sharing, equity, labor impacts, and the role of pilot evaluations. Finally, the report discusses technology developments with implications for the MOD ecosystem, such as shared automated vehicles (SAVs), urban air mobility (UAM), and last-mile delivery innovations. This report is a practical resource with: 1) current practices for planning and implementing MOD; 2) case studies and lessons learned; 3) considerations to help public agencies advance MOD in their communities; and 4) resources and recommended reading.

Read “Can Sharing Economy Platforms Increase Social Equity for Vulnerable Populations in Disaster Response and Relief? A Case Study of the 2017 and 2018 California Wildfires” by Stephen Wong, Jacquelyn Broader, and Susan Shaheen.

Ensuring social equity in evacuations and disasters remains a critical challenge for many emergency management and transportation agencies. Recent sharing economy advances – including transportation network companies (TNCs, also known as ridehailing and ridesourcing), carsharing, and homesharing – may supplement public resources and ensure more equitable evacuations. To explore the social equity implications of the sharing economy in disasters, we conducted four focus groups (n=37) of vulnerable populations impacted by California wildfires in 2017 or 2018. To structure these data, we employed the Spatial Temporal Economic Physiological Social (STEPS) equity framework in an evacuation context. We contribute to the literature by: 1) summarizing the focus groups and their opinions on the sharing economy in evacuations; 2) capturing wildfire evacuation obstacles through the STEPS transportation equity framework; and 3) linking STEPS and focus group results to explore the future potential of shared resources. Using STEPS, we also expand our shared resource exploration to 18 vulnerable groups.

We found that all focus groups were highly concerned with driver availability and reliability and the ability of vehicles to reach evacuation zones, not necessarily safety and security. Each group also expressed specific limitations related to their vulnerability. For example, individuals with disabilities were most concerned with inaccessible vehicles and homes. Using the STEPS framework, we found that while multiple vulnerable groups could gain considerable benefits from shared resources, 10 of the 18 groups experience three or more key challenges to implementation. We offer several policy recommendations to address equity-driven planning and shared resource limitations.

Read “Similarities and Differences of Mobility on Demand (MOD) and Mobility as a Service (MaaS)” by Susan Shaheen and Adam Cohen.

In cities around the world, innovative and emerging shared modes are offering residents, businesses, travelers, and other users more options to access mobility, goods, and services. As these shared modes build a network of services in many cities, consumers are increasingly engaging in more complex multimodal decision-making processes. Rather than making decisions between modes, travelers are “modal chaining” to optimize route, travel time, and cost. Additionally, digital information and fare integration are contributing to new on-demand access models for mobility and goods delivery.

On both sides of the Atlantic, two complementary approaches to multimodal access to public and private transportation services are evolving in parallel. In North America, consumers are assigning economic values to transportation services and making mobility decisions (including the decision not to travel and instead have a good or service delivered) based on cost, journey time, number 0f connections, convenience, and other attributes—a concept commonly referred to as mobility on demand (MOD). In Europe, services that allow travelers to sign up for mobility services in one bundled service are gaining popularity—a concept known as mobility as a service (MaaS). Practitioners are often faced with the questions: “What is MOD?” “What is MaaS?” and “How are MOD and MaaS similar and different?” This article aims to clarify these two concepts, explain their similarities and differences, and highlight a few public sector integrated mobility initiatives.

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Read “Shared ride services in North America: definitions, impacts, and the future of pooling” by Susan Shaheen and Adam Cohen.

Shared ride services allow riders to share a ride to a common destination. They include ridesharing (carpooling and vanpooling); ridesplitting (a pooled version of ridesourcing/transportation network companies); taxi sharing; and microtransit. In recent years, growth of Internet-enabled wireless technologies, global satellite systems, and cloud computing – coupled with data sharing – are causing people to increase their use of mobile applications to share a ride. Some shared ride services, such as carpooling and vanpooling, can provide transportation, infrastructure, environmental, and social benefits. This paper reviews common shared ride service models, definitions, and summarises existing North American impact studies. Additionally, we explore the convergence of shared mobility; electrification; and automation, including the potential impacts of shared automated vehicle (SAV) systems. While SAV impacts remain uncertain, many practitioners and academic research predict higher efficiency, affordability, and lower greenhouse gas emissions. The impacts of SAVs will likely depend on the number of personally owned automated vehicles; types of sharing (concurrent or sequential); and the future modal split among public transit, shared fleets, and pooled rides. We conclude the paper with recommendations for local governments and public agencies to help in managing the transition to highly automated vehicles and encouraging higher occupancy modes.

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Read “A Revealed Preference Methodology to Evaluate Regret Minimization with Challenging Choice Sets: A Wildfire Evacuation Case Study” by Stephen Wong, Caspar Chorus, Susan Shaheen, and Joan Walker.

Regret is often experienced for difficult, important, and accountable choices. Consequently, we hypothesize that random regret minimization (RRM) may better describe evacuation behavior than traditional random utility maximization (RUM). However, in many travel related contexts, such as evacuation departure timing, specifying choice sets can be challenging due to unknown attribute levels and near-endless alternatives, for example. This has implications especially for estimating RRM models, which calculates attribute-level regret via pairwise comparison of attributes across all alternatives in the set. While stated preference (SP) surveys solve such choice set problems, revealed preference (RP) surveys collect actual behavior and incorporate situational and personal constraints, which impact rare choice contexts (e.g., evacuations). Consequently, we designed an RP survey for RRM (and RUM) in an evacuation context, which we distributed from March to July 2018 to individuals impacted by the 2017 December Southern California Wildfires (n=226). While we hypothesized that RRM would outperform RUM for evacuation choices, this hypothesis was not supported by our data. We explain how this is partly the result of insufficient attribute-level variation across alternatives, which leads to difficulties in distinguishing non-linear regret from linear utility. We found weak regret aversion for some attributes, and we identified weak class-specific regret for route and mode choice through a mixed-decision rule latent class choice model, suggesting that RRM for evacuations may yet prove fruitful. We derive methodological implications beyond the present context toward other RP studies involving challenging choice sets and/or limited attribute variability.

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Read ‘“Three Ps in a MOD:” Role for mobility on demand (MOD) public-private partnerships in public transit provision‘ by Emma Lucken, Karen Trapenberg Frick, and Susan Shaheen.

The growing number of public transportation agencies partnering with Mobility on Demand (MOD) or Mobility as a Service (MaaS) companies raises the question of what role MOD companies can, should, and currently play in the provision of public transport. In this article, we develop a typology reflecting 62 MOD public-private partnerships (MOD PPPs) in the United States and present lessons learned. We conducted 34 interviews with representatives from four MOD companies and 27 public agencies. The interviews spanned October 2017 to April 2018. The resulting MOD PPP typology consists of four service models: 1) First-Mile/Last-Mile (FMLM), 2) Low Density, 3) Off-Peak, and 4) Paratransit. The typology also includes two MOD asset contribution models: 1) Agency-Operated MOD and 2) Agency-Subsidized Private MOD. Lessons learned for limiting competition with fixed-route public transit include: a) if agencies have sufficient resources, they can generally maintain greater data access and control over the service with Agency-Operated MOD than Agency-Subsidized Private MOD; b) public agencies can supplement the Agency-Operated MOD model with Agency-Subsidized Private MOD during peak demand; c) public agencies sometimes encourage FMLM transfers to fixed-route public transit by creating service zones that divide trip generators and attractors and assigning one or two designated transfer stops to each zone; and d) one approach to protecting fixed-route public transit is to restrict Low-Density MOD services to trips that start and end outside a geofenced fixed-route service area.

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Read “Bridging the Gap Between Evacuations and the Sharing Economy” by Stephen Wong, Joan Walker, PhD, and Susan Shaheen, PhD.

This paper examines the opportunities for addressing evacuations by leveraging the sharing economy. To support this research, we use a mixed-method approach employing archival research of sharing economy actions, 24 high-ranking expert interviews, and a survey of individuals impacted by Hurricane Irma in 2017 (n=645). Using these data, we contribute to the literature in four key ways. First, we summarize sharing economy company actions in 30 U.S. disasters. Second, we discuss results from 24 expert interviews on 11 sharing economy benefits (ranging from resource redundancy to positive company press coverage) and 13 limitations (ranging from driver reliability to the digital divide). Experts included six directors/executives of emergency/transportation agencies, two executives of sharing economy companies, and eight senior-level agency leaders. Third, we use these interviews, specifically negative opinions of the sharing economy, to inform our Hurricane Irma survey, which contributes empirical evidence of the feasibility of shared resources. Despite just 1.1% and 5.4% of respondents using transportation network companies (TNCs, also known as ridesourcing and ridehailing) and homesharing respectively during the Irma evacuation, some respondents were extremely willing to offer their own resources including transportation before evacuating (29.1%), transportation while evacuating (23.6%), and shelter for free (19.2%) in a future disaster. We also find spare capacity of private assets exists for future evacuations with just 11.1% and 16% of respondents without spare seatbelts and beds/mattresses, respectively. Finally, we conclude with practice-ready policy recommendations for public agencies to leverage shared resources including: communication partnerships, surge flagging (i.e., identifying and reducing unfair price increases), and community based sharing systems.

Read “Review of California Wildfire Evacuations from 2017 to 2019” by Stephen Wong, Jacquelyn Broader, and Susan Shaheen, PhD.

Between 2017 and 2019, California experienced a series of devastating wildfires that together led over one million people to be ordered to evacuate. Due to the speed of many of these wildfires, residents across California found themselves in challenging evacuation situations, often at night and with little time to escape. These evacuations placed considerable stress on public resources and infrastructure for both transportation and sheltering. In the face of these clear challenges, transportation and emergency management agencies across California have widely varying levels of preparedness for major disasters, and nearly all agencies do not have the public resources to adequately and swiftly evacuate all populations in danger. To holistically address these challenges and bolster current disaster and evacuation planning, preparedness, and response in California, we summarize the evacuations of eleven major wildfires in California between 2017 and 2019 and offer a cross-comparison to highlight key similarities and differences. We present results of new empirical data we collected via an online survey of individuals impacted by: 1) the 2017 October Northern California Wildfires (n=79), 2) the 2017 December Southern California Wildfires (n=226), and 3) the 2018 Carr Wildfire (n=284). These data reveal the decision-making of individuals in these wildfires including choices related to evacuating or staying, departure timing, route, sheltering, destination, transportation mode, and reentry timing. We also present results related to communication and messaging, non-evacuee behavior, and opinion of government response. Using the summarized case studies and empirical evidence, we present a series of recommendations for agencies to prepare for, respond to, and recover from wildfires.

Read “Fleeing from Hurricane Irma: Empirical Analysis of Evacuation Behavior Using Discrete Choice Theory” by Stephen Wong, Adam Pel, Susan Shaheen, and Caspar Chorus.

This paper analyzes the observed decision-making behavior of a sample of individuals impacted by Hurricane Irma in 2017 (n = 645) by applying advanced methods based in discrete choice theory. Our first contribution is identifying population segments with distinct behavior by constructing a latent class choice model for the choice whether to evacuate or not. We find two latent segments distinguished by demographics and risk perception that tend to be either evacuation-keen or evacuation-reluctant and respond differently to mandatory evacuation orders.

Evacuees subsequently face a multi-dimensional choice composed of concurrent decisions of their departure day, departure time of day, destination, shelter type, transportation mode, and route. While these concurrent decisions are often analyzed in isolation, our second contribution is the development of a portfolio choice model (PCM), which captures decision-dimensional dependency (if present) without requiring choices to be correlated or sequential. A PCM reframes the choice set as a bundle of concurrent decision dimensions, allowing for flexible and simple parameter estimation. Estimated models reveal subtle yet intuitive relations, creating new policy implications based on dimensional variables, secondary interactions, demographics, and risk-perception variables. For example, we find joint preferences for early-nighttime evacuations (i.e., evacuations more than three days before landfall and between 6:00 pm and 5:59 am) and early-highway evacuations (i.e., evacuations more than three days before landfall and on a route composed of at least 50% highways). These results indicate that transportation agencies should have the capabilities and resources to manage significant nighttime traffic along highways well before hurricane landfall.

Read “Shared Mobility Policy Playbook” by Susan Shaheen, PhD, Adam Cohen, Michael Randolph, Emily Farrar, Richard Davis, and Aqshems Nichols.

The Shared Mobility Policy Playbook provides an introduction and definitions of shared mobility services, mode-specific resources for agencies looking to develop policies in their community, and policy-focused tools demonstrating case studies and best practices for shared mobility.

This playbook has been designed for individuals and practitioners who want to know more about shared mobility and to communities interested in incorporating shared mobility into their transportation ecosystem. It is a practical guide with resources, information, and tools for local governments, public agencies, and non-governmental organizations seeking to incorporate and manage innovative and emerging shared mobility services. The following are suggested uses of this playbook:

  • Access shared mobility resources including: opportunities, lessons learned, and best practices for deploying shared mobility across the United States.
  • Use this playbook as a guide for strategic transportation planning and incorporating shared mobility into transportation plans and models.
  • Reference best practices, lessons learned, and case studies to aid public policy development.

Read “Social Equity Impacts of Congestion Management Strategies” by Susan Shaheen, PhD, Adam Stocker, and Ruth Meza.

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.

Read “Current State of the Sharing Economy and Evacuations: Lessons from California” by Stephen Wong and Susan Shaheen, PhD.

In many evacuations including wildfire evacuations, public agencies often do not have enough resources to evacuate and shelter all citizens. Consequently, we propose that the sharing economy, through private companies and/or private citizens, could be leveraged in disasters for transportation and sheltering resources. To assess this feasibility, we distributed surveys to individuals impacted by three major wildfires in California: 1) the 2017 October Northern California Wildfires (n=79), 2) the 2017 December Southern California Wildfires (n=226), and 3) the 2018 Carr Wildfire (n=284). Using these data, we find that private citizens are moderately to highly likely to share transportation and sheltering resources in future disasters, but numerous reservations persist about sharing. We also find significant spare capacity in evacuating vehicles and potential homes. To supplement this work, we also conducted four focus groups (n=37) of vulnerable populations to determine the benefits and limitations of a sharing economy strategy in terms of equity. Groups included low-income (2017 December Southern California Wildfires), older adult (2017 October Northern California Wildfires), individuals with disabilities (2017 October Northern California Wildfires), and Spanish-speaking (2018 Mendocino Complex Wildfire). We find that while severe equity limitations exist, groups were able to develop several recommendations for successfully leveraging sharing economy resources for the general population and their specific vulnerable group. We conclude with several local agency and statewide recommendations for building a sharing economy framework for California to prepare for future evacuations.

Read “Shared Micromobility Policy Toolkit: Docked and Dockless Bike and Scooter Sharing” by Susan Shaheen, PhD and Adam Cohen.

This toolkit outlines policies and practices for cities integrating shared micromobility into the built environment. The toolkit is divided into four sections that: 1) define shared micromobility and its impacts, 2) describe users of shared micromobility and market potential, 3) review best practices and case studies for curb space management and related policies, and 4) provide a summary of key findings from the toolkit.

Read “One-Way Electric Vehicle Carsharing in San Diego: An Exploration of the Behavioral Impacts of Pricing Incentives on Operational Efficiency” by Susan Shaheen, Ph.D., Elliot Martin, Ph.D., and Apsaar Bansal.

This project is a two-year evaluation of pricing/incentives applied to the one-way, all electric carsharing system operated by car2go in San Diego, CA. This system is the only electric vehicle-based, one-way carsharing system with instant access (i.e., accessible without reservation) operating in the U.S. The goal of this project is to work with car2go and the San Diego region to develop and evaluate pricing/incentive structures for their members, which improve system operational efficiency (vehicle redistribution, state-of-charge management, use of vehicles placed at public transit stations) and encourage shared-vehicle use.

 

Read “Understanding Evacuee Behavior: A Case Study of Hurricane Irma” by Stephen Wong; Susan Shaheen, PhD; and Joan Walker, PhD.

 

In September 2017, Hurricane Irma prompted one of the largest evacuations in U.S. history of over six million people. This mass movement of people, particularly in Florida, required considerable amounts of public resources and infrastructure to ensure the safety of all evacuees in both transportation and sheltering. Given the extent of the disaster and the evacuation, Hurricane Irma is an opportunity to add to the growing knowledge of evacuee behavior and the factors that influence a number of complex choices that individuals make before, during, and after a disaster. At the same time, emergency management agencies in Florida stand to gain considerable insight into their response strategies through a consolidation of effective practices and lessons learned. To explore these opportunities, we distributed an online survey (n = 645) across Florida with the help of local agencies through social media platforms, websites, and alert services. Areas impacted by Hurricane Irma were targeted for survey distribution. The survey also makes notable contributions by including questions related to reentry, a highly under-studied aspect of evacuations. To determine both evacuee and non-evacuee behavior, we analyze the survey data using descriptive statistics and discrete choice models. We conduct this analysis across a variety of critical evacuation choices including decisions related to evacuating or staying, departure timing, destination, evacuation shelter, transportation mode, route, and reentry timing.

Read “California Transportation Plan 2050: Northern and Southern California Visioning Sessions Findings” by Susan Shaheen, PhD, Hannah Totte, and Adam Cohen. Improving California’s transportation system requires cross-sector collaboration, particularly as technologies, policies, and regulations develop simultaneously. The California Transportation Plan (CTP) 2050 aims to integrate perspectives a diverse array of stakeholder perspectives that may not typically participate in the statewide planning process. The Visioning Sessions facilitated two day-long visioning workshops in October 2018 in Southern and Northern California. Overall, these visioning sessions initiated a much-needed dialogue among experts and practitioners from diverse backgrounds and allowed participants to conceptualize idealized visions for California’s transportation system through 2050. Key goals of the visioning sessions included: 1. Developing visions for CTP2050 incorporating diverse perspectives from an array of statewide stakeholders including private and public sector, academic, and non-profit experts; 2. Identifying existing and policy and investment strategies to actualize the idealized states; and 3. Translating high-level policy and investment suggestions into actionable items.
Read “The Benefits of Carpooling” by Susan Shaheen, PhD, Adam Cohen, and Alexandre Bayen. Carpooling allows travelers to share a ride to a common destination and can include several forms of sharing a ride, such as casual carpooling and real-time carpooling. Because carpooling reduces the number of automobiles needed by travelers, it is often associated with numerous societal benefitsincluding: 1) reductions in energy consumption and emissions, 2) congestion mitigation, and 3) reduced parking infrastructure demand. In recent years, economic, environmental, and social forces coupled with technological innovations are encouraging shared and pooled services. Shared mobility is changing how people travel and is having a transformative impact on mobility. This chapter reviews key trends impacting the mobility marketplace including the growth of shared mobility and key demographic indicators, such as an aging population and Millennials entering the workforce. For decades, carpooling has been used as a strategy by numerous public agencies and employers as a strategy to address a range of climate, environmental, and congestion mitigation goals, while simultaneously increasing roadway and parking capacity. This chapter discusses how employers and public agencies can support carpooling. This chapter concludes with a summary of key findings from the report.
Read “Managing the Transition to Shared Automated Vehicles: Building Today While Designing for Tomorrow” by Susan Shaheen, PhD and Adam Cohen in Meeting of the Minds.  We often get asked questions from urban planners, policymakers, and real estate professionals asking how they should prepare for the future of mobility, today. Some are architects and developers wanting to know how their buildings and planned communities should be designed in a shared automated future. Some are planners and policymakers wanting to know if and how their zoning and building codes should be amended to prepare. In an automated future, cities could change in three fundamental ways:

  1. The density of urban centers is likely to increase.
  2. Suburban and exurban areas are likely to expand.
  3. A reduction in parking is likely.

Read “Big Data, Automation, and the Future of Transportation” by Susan Shaheen, PhD, and Adam Cohen in Meeting of the Minds.  In recent years, a variety of forces (economic, environmental, and social) have quickly given rise to “shared mobility,” a collective of entrepreneurs and consumers leveraging technology to share transportation resources, save money, and generate capital. Bikesharing services, such as BCycle, and business-to-consumer carsharing services, such as Zipcar, have become part of a sociodemographic trend that has pushed shared mobility from the fringe to the mainstream. The role of shared mobility in the broader landscape of urban mobility has become a frequent topic of discussion. Shared transportation modes—such as bikesharing, carsharing, ridesharing, ridesourcing/transportation network companies (TNCs), and microtransit—are changing how people travel and are having a transformative effect on smart cities.
Read “Understanding How Cities Can Link Smart Mobility Priorities Through Data” by Susan Shaheen, PhD, Elliot Martin, PhD, Mikaela Hoffman-Stapleton, and Peter Slowik. This white paper presents a generalized evaluation framework that can be used for assessing project impacts within the context of transportation-related city projects. In support of this framework, we discuss a selection of metrics and data sources that are needed to evaluate the performance of smart city innovations. We first present a collection of projects and applications from near-term smart city concepts or actual pilot projects underway (i.e., Smart City Challenge, Federal Transit Administration (FTA) Mobility on Demand (MOD) Sandbox, and other pilot projects operating in the regions of Los Angeles, Portland, and San Francisco). These projects are identified and explained in Section 2 of this report. Using these projects as the basis for hypothetical case studies, we present selected metrics that would be necessary to evaluate and monitor the performance of such innovations over time. We then identify the data needs to compute those metrics and further highlight the gaps in known data resources that should be covered to enable their computation. The objective of this effort is to help guide future city planners, policy makers, and practitioners in understanding the design of key metrics 3 and data needs at the outset of a project to better facilitate the establishment of rigorous and thoughtful data collection requirements.
Read “Peer-To-Peer (P2P) Carsharing: Understanding Early Markets, Social Dynamics, and Behavioral Impacts” by Susan Shaheen, PhD, Elliot Martin, PhD, and Apaar Bansal.

 
Shared mobility services have now become firmly integrated into urban transportation systems across the globe. Carsharing, bikesharing, ridesourcing or transportation network companies (TNCs), and other systems now offer urban travelers access to transportation services that had long been previously only possible through personal vehicle ownership. Carsharing is arguably the pioneer mode of the sharing economy, given it ushered in a new way of thinking and access to the private automobile in the 20th century. Since its North American inception in Montreal in 1994, carsharing has undergone several waves of innovation. With each innovation, carsharing has deployed new functionality, technology, and business models. One of the more prominent innovations in carsharing has been peer-to-peer (P2P) carsharing, which enables individuals to leverage information technology to share their personal vehicles with others in their area. The P2P carsharing industry has gone through some evolution of its own since its initial establishment.
Read “Transportation Research Circular: U.S. Department of Transportation’s Mobility on Demand Initiative” by Susan Shaheen, PhD, Adam Cohen, and Elliot Martin, PhD. The market for personal mobility is changing rapidly due to shifting social and cultural trends, as well as technological advances such as smartphones, information processing, and widespread data connectivity. Mobility on Demand (MOD) is an innovative transportation concept. On the supply side, transportation providers manage mobility rather than traffic through demand-responsive service, shifting use to alternate modes. On the demand side, mobility consumers reserve, dispatch, or use innovative mobility, public transportation, and goods delivery strategies in place of privately owned vehicles. The most-advanced forms of MOD incorporate trip planning and booking, real-time information, and fare payment into a single-user interface. Modes facilitated through MOD providers can include carsharing, bikesharing, ridesharing, ridesourcing, or transportation network companies (TNCs), scooter sharing, microtransit, shuttle services, public transportation, and other emerging transportation solutions.
Listen to “The Mobility Podcast” with Susan A. Shaheen, as she discusses the recent report: “Travel Behavior: Shared Mobility and Transportation Equity.”  This episode was recorded live at the Next Urbanism Conference, in Portland, OR.
Read “Future of Mobility White Paper” as part of CALTRANS California Transportation Plan 2050, by Susan Shaheen, PhD, Hannah Totte, and Adam Stocker. 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).
Read “Mobility on Demand: Operational Concept Report” by Susan Shaheen, PhD, Adam Cohen, Balaji Yelchuru, and Sara Sarkhili.

This operational concept report provides an overview of the Mobility on Demand (MOD) concept and its evolution, description of the MOD ecosystem in a supply and demand framework, and its stakeholders and enablers. Leveraging the MOD ecosystem framework, this report reviews the key enablers of the system including business models and partnerships, land use and different urbanization scenarios, social equity and environmental justice, policies and standards, and enabling technologies. This review is mostly focused on the more recent forms of MOD (e.g., shared mobility).

Read “Travel Behavior: Shared Mobility and Transportation Equity” by Susan Shaheen, PhD, Corwin Bell, Adam Cohen, and Balaji Yelchuru. Shared mobility—the shared use of a motor vehicle, bicycle, or other low-speed transportation mode that allows users to obtain short-term access to transportation on an as-needed basis—has the potential to help address some transportation equity challenges. In an effort to categorize the myriad of transportation equity barriers facing transportation system users, this primer proposes a ‘STEPS to Transportation Equity’ framework including: Spatial, Temporal, Economic, Physiological, and Social barriers. For each barrier category, shared mobility opportunities and challenges are explored along with policy recommendations.
Read “Shared Mobility: Current Practices and Guiding Principles” by Susan Shaheen, PhD, Adam Cohen, and Ismail Zohdy. This primer provides an introduction and background to shared mobility; discusses the government’s role; reviews success stories; examines challenges, lessons learned, and proposed solutions; and concludes with guiding principles for public agencies. The primer provides an overview of current practices in this emerging field, and it also looks toward the future in the evolution and development of shared mobility. Two-page Overiew Glossary of Shared Mobility Terms
Read “Mobile Apps and Transportation: A Review of Smartphone Apps and a Study of User Response to Multimodal Traveler Information” by Susan Shaheen, PhD, Elliot Martin, PhD, Adam Cohen, Apoorva Musunuri, and Abhinav Bhattacharyya. In recent years, technological and social forces have pushed smartphone applications (apps) from the fringe to the mainstream. Understanding the role of transportation apps in urban mobility is important for policy development and transportation planners. This study evaluates the role and impact of multimodal aggregators from a variety of perspectives, including a literature review; a review of the most innovative, disruptive, and highest-rated transportation apps; interviews with experts in the industry, and a user survey of former multimodal aggregator RideScout users. Between February and April 2016, researchers conducted interviews with experts to gain a stronger understanding about challenges and benefits of data sharing between private companies and public agencies. Key findings from the expert interviews include the critical need to protect user privacy; the potential to use data sharing to address integrated corridor and congestion management as well as various pricing strategies during peak hours; along with the potential benefits for improving coordination between the public and private sectors. In March 2016, researchers surveyed 130 people who had downloaded the RideScout app to evaluate attitudes and perceptions toward mobile apps, travel behavior, and modal shift. The goal was to enhance understanding of how the multimodal apps were impacting the transportation behavior. The survey did found that respondents used multimodal apps in ways that yielded travel that was less energy intensive and more supportive of public transit. Looking to the future, smartphone applications and more specifically multimodal aggregators, may offer the potential for transportation planners and policymakers to enhance their understanding of multimodal travel behavior, share data, enhance collaboration, and identify opportunities for public-private partnerships.
cover page for Zipcar college travel study
Read “North American College/University Market Carsharing Impacts: Results from Zipcar’s College Travel Study 2015” by Adam Stocker, Jessica Lazarus, Sophia Becker, and Susan Shaheen, PhD.

Researchers at the Transportation Sustainability Research Center (TSRC), UC Berkeley in partnership with Zipcar conducted a survey to better understand the impact that carsharing has on college member travel behavior, vehicle holdings and driving, quality of life, and transportation expense savings. The survey design was conducted as a joint effort among TSRC, Zipcar, and university representatives. The college/university carsharing market is a unique environment for both carsharing users and operators. Due to the particular living arrangements and travel needs of college members, carsharing usage on college/university campuses and the impacts of carsharing are different than the neighborhood carsharing market. One major distinction between college carsharing and carsharing in the general population is the difference between household and individual vehicle holdings and transportation decisions. Since many college students do not live in a typical household setting, impacts regarding vehicles and driving must be assessed on an individual basis (in contrast to the household level) for a majority of these users. The methodology employed in this survey accounts for this important distinction, whereas most of the previous carsharing studies use the household as the common unit of measurement.
Read “Impacts of Car2go on Vehicle Ownership, Modal Shift, Vehicle Miles Traveled, and Greenhouse Gas Emissions: An Analysis of Five North American Cities” by Elliot Martin, PhD and Susan Shaheen, PhD. This study was designed to better understand how car2go is used; how it changes travel behavior; and its impacts on vehicle ownership, driving, and greenhouse gas (GHG) emissions. Car2go is a one-way carsharing service provider with a free-floating operational model, primarily. Between 2014 and 2015, we distributed an online survey to car2go members in the cities of San Diego, Seattle, Vancouver, Calgary, and Washington, D.C. Across all cities, the survey was completed by 9,497 car2go members. Based on an analysis of the survey and car2go activity data, we estimate the impacts that car2go has had on vehicles sold and suppressed by car2go members, modal shift, vehicle miles traveled (VMT), and GHG emissions within the five cities during the year the surveys were deployed.

This working paper has six sections including: 1) methodological overview, 2) impact of car2go on vehicle holdings, 3) car2go impacts on modal shift, 4) car2go and estimated changes in VMT, 5) GHG emission impacts, and 6) key takeaways.
Read “Smartphone Applications to Influence Travel Choices: Practices and Policies” by Susan Shaheen, PhD, Adam Cohen, Ismail Zohdy, and Beaudry Kock. This primer provides an overview of current practices in this emerging field and looks toward the future in the evolution and development of smartphone applications for the transportation sector. The primer provides an introduction and overview smartphone applications (known as “apps”); discusses the background, evolution, and development of smartphone apps; reviews the types of smartphone applications promoting transportation efficiency and congestion reduction; discusses transportation apps and their impacts on traveler behavior; examines current challenges; and concludes with guiding principles for public agencies. Two-page Overview
Read “Shared Mobility: Definitions, Industry Developments, and Early Understanding” by Susan Shaheen, PhD, Nelson Chan, Apaar Bansal, and Adam Cohen. This white paper includes an introduction and background to different types of shared modes, as well as smartphone-based trip planning apps that can facilitate access to public transit and shared mobility services. This paper also notes where potential benefits of shared mobility could align with the new mission of the California Department of Transportation (Caltrans), which is to “Provide a safe, sustainable, integrated, and efficient transportation system to enhance California’s economy and livability.” We conclude the paper with a summary and provide an appendix with a glossary of terms and a list of the shared mobility models, including a range of companies in each sector.
Read “Zero- and Low-Emission Vehicles in U.S. Carsharing Fleets: Impacts of Exposure on Member Perceptions” by Susan Shaheen, PhD, Elliot Martin, PhD, and Apaar Bansal.

The California Zero-Emission Vehicle (ZEV) Mandate, adopted in 1990, was aimed at increasing the sale and dissemination of low- or zero-emission vehicles throughout the California auto market. ZEVs include plug-in hybrid vehicles (PHVs) and all-electric vehicles (EVs). In an attempt to accelerate the exposure of ZEVs in the general population, in 2001, additional credits were allotted to automakers in return for placing ZEVs into transportation networks, such as carsharing fleets. This policy is set to end in 2018. This white paper presents the results of a study that evaluated the impacts of ZEV exposure on United States carsharing users. Two surveys were administered to members of several car sharing organizations that use PHVs or EVs in their fleet including: car2go, DriveNow, eGo, and Zipcar. One was a control group survey, which was comprised of 1,742 respondents, and the other was an experimental group survey, covering 1,920 respondents.

The results support that exposure to PHVs or EVs through carsharing has influenced customer ZEV perceptions to be more positive and has commensurately increased the propensity for an individual to buy a ZEV. Furthermore, the data suggest that certain socio-demographic groups, such as younger people and women, are more interested in purchasing these vehicles after using them in carsharing.

Read “Shared Mobility: Retrospective from Caltrans Shared Mobility Workshop” by Susan Shaheen, PhD, Adam Stocker, and Apaar Bansal.

On September 8, 2015, UC Berkeley’s Transportation Sustainability Research Center (TSRC), in partnership with the California Department of Transportation (Caltrans), hosted “Shared Mobility: A Sustainability and Technologies Workshop” at the UC Davis Conference Center. The workshop facilitated a dialogue among nearly 100 participants representing 28 organizations. There were 61 attendees from Caltrans, with 38 from Headquarters and 23 from various district offices. Caltrans employee attendees included planners, engineers, researchers, managers, and directors. In addition, nine participants were from the private sector and included individuals from shared mobility companies. There were 27 participants from other public agencies and universities.
This synopsis covers findings and discussions from the conference, and it summarizes the key topics explored throughout the day. The report starts off with recaps of the workshop introductions from Professor Susan Shaheen of UC Berkeley, Steve Cliff of Caltrans, and Socorro “Coco” Briseno of Caltrans. Next, the two expert panels are discussed in detail, touching upon key points made by each panel member and moderator. The breakout sessions are then covered, and the discussions regarding the impacts of shared mobility and on Caltrans planning and operations are reviewed. Finally, a conclusion summarizes the overall findings and key takeaways from the workshop.
Read “Shared-Use Mobility Summit: Retrospective from North America’s first gathering on shared-use mobility” by Susan Shaheen, PhD, and Matt Christensen. Shared-use mobility-the shared use of a vehicle, bicycle or other low-speed mode-is an innovative transportation solution that enables users to have short-term access to a transportation mode. In North America, shared-use mobility encompasses the submarkets of carsharing, bikesharing, ridesharing, on-demand ride services, scooter sharing, shuttle services, and other emerging industries. In October 2013, the University of California, Berkeley’s Transportation Sustainability Research Center (TSRC) hosted the inaugural Shared-Use Mobility Summit in San Francisco, California. The summit was a two-day event that facilitated a dialogue among nearly 300 participants representing close to 200 organizations. Participants included mobility providers, policymakers, governmental agencies, non-profits, technologists, academics, media, other stakeholders, and affiliated industries. One hundred and five (105) private companies attended the summit, and 62 governmental agencies were represented at the summit. Additionally, 44 academics from 17 universities participated. Of the 194 organizations represented, 26 were affiliated with carsharing, 16 with bikesharing, and 6 were associated with ridesharing and ondemand ride services or transportation network companies (TNCs).
Read “Disrupting Mobility: Impacts of Sharing Economy and Innovative Transportation on Cities,” edited by Susan Shaheen, PhD, and Gereon Meyer.  This book explores the opportunities and challenges of the sharing economy and innovative transportation technologies with regard to urban mobility. Written by government experts, social scientists, technologists and city planners from North America, Europe and Australia, the papers in this book address the impacts of demographic, societal and economic trends and the fundamental changes arising from the increasing automation and connectivity of vehicles, smart communication technologies, multimodal transit services, and urban design.
Read “Planning for Shared Mobility” by Susan Shaheen, PhD, and Adam Cohen. In recent years, economic, environmental, and social forces have quickly given rise to the “sharing economy,” a collective of entrepreneurs and consumers leveraging technology to share resources, save money, and generate capital. Homesharing services, such as Airbnb, and peer-to-peer carsharing services, such as Getaround, have become part of a sociodemographic trend that has pushed the sharing economy from the fringe and more to the mainstream. The role of shared mobility in the broader landscape of urban mobility has become a frequent topic of discussion. Major shared transportation modes—such as bikesharing, carsharing, ridesourcing, and alternative transit services—are changing how people travel and are having a transformative effect on mobility and local planning.
Read “Mobility and the Sharing Economy: Impacts Synopsis” by Susan Shaheen, PhD, and Nelson Chan.

Shared Mobility – the shared use of a vehicle, bicycle, or other low-speed mode – is an innovativetransportation solution that enables users to have short-term access to transportation modes on an “as-needed” basis. Shared mobility includes carsharing, personal vehicle sharing (or peer-to-peer (P2P) carsharing), bikesharing, scooter sharing, shuttle services, ridesharing, and on-demand ride services. It can also include commercial delivery vehicles providing flexible goods movement. Shared mobility has had a transformative impact on many global cities by enhancing transportation accessibility while simultaneously reducing ownership of personal automobiles. In the context of carsharing and bikesharing, vehicles and bicycles are typically unattended, concentrated in a network of locations where the transaction of checking out a vehicle or bicycles is facilitated through information technology (IT) and other technological innovations. Usually, carsharing and bikesharing operators are responsible for the cost of maintenance, storage, parking, and insurance/fuel (if applicable). In the context of classic ridesharing (carpooling and vanpooling) and on-demand ride services, such as transportation network companies (TNCs), many of these providers employ IT to facilitate the matching of riders and drivers for trip making.

Read “Shared Mobility: Current Practices and Guiding Principles – Glossary” by Susan Shaheen, PhD, and Adam Cohen. Includes definitions for: Alternative Transit Services, Bikesharing, Carpooling, Car Rental, Carsharing, Closed-Campus Bikesharing, Courier Network Services, E-Hail Apps, High-Tech Company Shuttles, Fixed Route and Fixed Schedule Microtransit, Flexible Route and On-Demand Schedule Microtransit, Flexible Transit Services, Fractional Ownership, Hybrid Peer-to-Peer, Limousines and Liveries, Microtransit, One-Way Carsharing, Paired On-Demand Passenger Ride and Courier Services, Pedicabs, Peer-to-Peer Access Model, Peer-to-Peer Carsharing, Peer-to-Peer Marketplace, Personal Vehicle Sharing, Public Transportation, Peer-to-Peer Bikesharing, Transportation Network Company/Ridesourcing, Ride-Hailing, Ridesplitting, Rountrip Carsharing, Scooter Sharing, Slugging, Taxis, and Vanpooling.
Read “Shared Mobility: Current Practices and Guiding Principles – Glossary” by Susan Shaheen, PhD, and Adam Cohen. Includes definitions for: Alternative Transit Services, Bikesharing, Carpooling, Car Rental, Carsharing, Closed-Campus Bikesharing, Courier Network Services, E-Hail Apps, High-Tech Company Shuttles, Fixed Route and Fixed Schedule Microtransit, Flexible Route and On-Demand Schedule Microtransit, Flexible Transit Services, Fractional Ownership, Hybrid Peer-to-Peer, Limousines and Liveries, Microtransit, One-Way Carsharing, Paired On-Demand Passenger Ride and Courier Services, Pedicabs, Peer-to-Peer Access Model, Peer-to-Peer Carsharing, Peer-to-Peer Marketplace, Personal Vehicle Sharing, Public Transportation, Peer-to-Peer Bikesharing, Transportation Network Company/Ridesourcing, Ride-Hailing, Ridesplitting, Rountrip Carsharing, Scooter Sharing, Slugging, Taxis, and Vanpooling.