Symposium on the Sharing Economy


Research Workshop Session II: Shared Mobility

Cloud Commuting and Mobility-as-a-Service (MaaS) Transport

With the advent of automated vehicles, Mobility-as-a-Service (MaaS)—including taxi, ridesharing, ridesourcing, carsharing, and bikesharing—has the potential to rise from a niche player in modern transport in most U.S. cities to an important contributor in how people get around. This talk, extracted from the recent book The End of Traffic and the Future of Transport, positioned MaaS within the emerging transport sector and looked at its potential scope and implications, particularly for land use, and limitations.

David Levinson serves on the faculty of the Department of Civil, Environmental, and Geo- Engineering at the University of Minnesota, is Managing Director of the Accessibility Observatory, and directs the Networks, Economics, and Urban Systems (NEXUS) research group. He holds the Richard P. Braun/CTS Chair in Transportation. He also serves on the graduate faculty of the Applied Economics and Urban and Regional Planning programs at the University of Minnesota. In academic year 2006-2007, he was a visiting academic at Imperial College in London.

In January 2005, he was awarded the CUTC/ARTBA New Faculty Award. He earned a Ph.D. in transportation engineering at the University of California at Berkeley in 1998. His dissertation “On Whom the Toll Falls,” argues that local decision making about managing and financing roads will most likely lead to direct road pricing, which will allow the efficient allocation of scarce road resources (and thus reduce congestion). He has also conducted research into travel behavior. Levinson has authored or edited several books, including The Transportation ExperiencePlanning for Place and Plexus, and The End of Traffic and the Future of Transport, and numerous peer reviewed articles. He is the editor of the Journal of Transport and Land Use

Service Region Design for Urban Electric Vehicle Sharing Systems

Emerging collaborative consumption business models have shown promise in both generating business opportunities and enhancing efficient use of resources. In the transportation domain, carsharing models are being adopted at mass scales in major metropolitan areas worldwide. This mode of servicized mobility bridges the resource efficiency of public transit and the flexibility of personal transportation. Beyond significant potential to reduce car ownership, carsharing shows promise in supporting adoption of fuel efficient vehicles, such as electric vehicles (EVs), due to these vehicles’ special cost structure with high purchase but low operating costs. Recently, it has become a trend for key players in the carsharing business, such as Car2Go and Autolib, to employ EVs in an operations model that accommodates one-way trips. On the one hand, the one-way model brings about significant improvements in coverage of travel needs, and therefore adoption potential, compared with the conventional round-trip-only model (advocated by ZipCar, for example). On the other hand, it poses tremendous planning and operational challenges.

This presentation reviewed a study of the planning problem faced by carsharing service providers in designing the geographical service region in which to operate the service. This decision encompasses the trade-off between maximizing customer catchment by covering travel needs and controlling fleet operations costs. The presentation also reviewed the development of a mathematical programming model that incorporates details of both customer adoption behavior and fleet management (including EV repositioning and charging) under spatially imbalanced and time-varying travel patterns. To address inherent planning uncertainty with regard to adoption patterns, the researchers employed a distributionally robust optimization framework that informs robust decisions to avoid possible ambiguity (or lack) of data. Mathematically, the problem can be approximated by a mixed integer second-order cone program, which is computationally tractable with practical scale data. The presentation also included an overview of how this approach was applied to the case of Car2Go's service in San Diego, California, with real operations data, addressing a number of planning questions and suggesting potential for future development of the service.

Ho-Yin Mak is an associate professor in management science at Saïd Business School and fellow at St Cross College, Oxford. His research focuses on the analysis of operations and planning problems arising in domain areas such as supply chain management, sustainable operations, transportation, and health care. He has an undergraduate degree from Northwestern University and master's and doctoral degrees from the University of California at Berkeley. Prior to joining Saïd Business School in 2015, he served on the faculty of the Hong Kong University of Science & Technology.

Peer-to-Peer Carsharing Market Analysis and Potential Growth

Many studies show that carsharing reduces transportation costs for a large segment of the population. Carsharing also reduces the number of private vehicles on the road because carshare members do not purchase their own cars. However, the traditional carsharing business model is difficult to scale geographically to neighborhoods with lower population densities because the operator must bear the upfront fixed cost of purchasing or leasing the vehicles in the fleet. In contrast to traditional carsharing, peer-to-peer (P2P) carsharing allows car owners to convert their personal vehicles into shared cars that can be rented to other drivers on a short-term basis. This model helps to improve the situation in which most privately owned vehicles sit idle more than 90 percent of the day. P2P carsharing alleviates upfront costs and thus is more economically consistent with lower-density neighborhoods than traditional carsharing. As a result, P2P carsharing provides greater potential for car accessibility than traditional carsharing does.

Several new service companies are dedicated to P2P carsharing. A methodology was developed to assess the market feasibility of P2P carsharing. This presentation described a methodology that was developed to assess the market feasibility of P2P carsharing. The market for P2P carsharing was found to be economically viable. However, uncertain and fragmented public policy and car insurance regimes threatened the growth and investment in P2P carsharing.

Robert Hampshire is an assistant research professor in the Human Factors Group at the University of Michigan Transportation Research Institute. He was previously an assistant professor of operations research and public policy at the H. John Heinz III College at Carnegie Mellon University. He received a Ph.D. in operations research and financial engineering from Princeton University in 2007. His research focuses on management, modeling, and optimization of services. His work considers mobility services such as smart parking, connected vehicles, ride sharing, bike sharing, carsharing and person-2-person carsharing. This work is supported by the National Science Foundation, Department of Transportation and several nonprofit foundations. He uses stochastic modeling, simulation, and dynamic optimization to develop design and management strategies. More specifically, his methodological interests are dynamic control of transient stochastic systems, queueing networks with time-varying rates, and asymptotic approximations (strong approximations).

How Should Planners Prepare for Autonomous Cars?

In recent years, nearly all major automobile manufacturers and many technology firms have announced remarkable breakthroughs in the development of autonomous cars and trucks. Automated vehicle fleets should lead to significant improvements in traffic safety and congestion while taking advantage of existing ubiquitous road networks rather than requiring new infrastructure. For these and other reasons, traffic engineers, urban planners, and economists are bullish on the future of these vehicles.

Yet along with extremely optimistic predictions that these technologies will be transformative for cities, there has been a great deal of handwringing about what, exactly, planners’ roles are for managing the deployment of new automated driving technology. While many planners have taken the position that this new technology will revolutionize passenger travel and metropolitan form, this presentation posited that automated driving should be viewed in evolutionary terms and that to plan for automated cars planners should focus on the same issues that they face today. In this view, the future of transportation in cities remains a future shaped by political forces rather than technological ones. By focusing on the technological change, planners risk marginalizing their own role in shaping the future.

David King is currently an assistant professor of urban planning in the Graduate School of Architecture, Planning and Preservation at Columbia University, and this fall he will be moving to the School of Geographical Sciences and Urban Planning at Arizona State University. He teaches and researches transportation and land-use planning, transportation finance, and planning research methods. In his research, King focuses on municipal-level transportation policies such as parking management and taxi services, which are policy areas that affect traffic performance as well as quality of life. His work on transportation finance examines ways that local and regional planning can use existing and new finance tools to raise revenues for more effective and just transportation systems. Prior to joining Columbia in 2008, David completed his Ph.D. at UCLA and a master's in urban and regional planning at the Humphrey Institute at the University of Minnesota. His current research focuses on taxi and jitney services, informal transit, street design, and how new technologies affect transportation finance and local policy.