Carsharing programs that operate as short-term vehicle rentals (often for one-way trips before ending the rental) like Car2Go and ZipCar have quickly expanded, with the number of US users doubling every 1–2 years over the past decade. Such programs seek to shift personal transportation choices from an owned asset to a service used on demand. The advent of autonomous or fully self-driving vehicles will address many current carsharing barriers, including users’ travel to access available vehicles. This work describes the design of an agent-based model for shared autonomous vehicle (SAV) operations, the results of many case-study applications using this model, and the estimated environmental benefits of such settings, versus conventional vehicle ownership and use. The model operates by generating trips throughout a grid-based urban area, with each trip assigned an origin, destination and departure time, to mimic realistic travel profiles. A preliminary model run estimates the SAV fleet size required to reasonably service all trips, also using a variety of vehicle relocation strategies that seek to minimize future traveler wait times. Next, the model is run over one-hundred days, with driverless vehicles ferrying travelers from one destination to the next. During each 5-min interval, some unused SAVs relocate, attempting to shorten wait times for next-period travelers. Case studies vary trip generation rates, trip distribution patterns, network congestion levels, service area size, vehicle relocation strategies, and fleet size. Preliminary results indicate that each SAV can replace around eleven conventional vehicles, but adds up to 10% more travel distance than comparable non-SAV trips, resulting in overall beneficial emissions impacts, once fleet-efficiency changes and embodied versus in-use emissions are assessed.

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The travel and environmental implications of shared autonomous vehicles, using agent-based model scenarios

Considerable interest exists in modeling and forecasting the effects of autonomous vehicles on travel behavior and transportation network performance. In an autonomous vehicle (AV) future, individuals may privately own such vehicles, use mobility-on-demand services provided by transportation network companies that operate shared AV fleets, or adopt a combination of those two options. This paper presents a comprehensive model system of AV adoption and use. A generalized, heterogeneous data model system was estimated with data collected as part of the Puget Sound, Washington, Regional Travel Study. The results showed that lifestyle factors play an important role in shaping AV usage. Younger, urban residents who are more educated and technologically savvy are more likely to be early adopters of AV technologies than are older, suburban and rural individuals, a fact that favors a sharing-based service model over private ownership. Models such as the one presented in this paper can be used to predict the adopti...

Modeling Individual Preferences for Ownership and Sharing of Autonomous Vehicle Technologies

This study proposes an interesting electric vehicle fleet size and trip pricing (EVFS&TP) problem for one-way carsharing services by taking into account the necessary practical requirements of vehicle relocation and personnel assignment. The EVFS&TP problem aims to maximize the profit of one-way carsharing operators by determining the electric vehicle fleet size, trip pricing, and strategies of vehicle relocation and personnel assignment subject to the elastic demand for the one-way carsharing services. A mixed-integer nonlinear and nonconvex programming model is first built for the EVFS&TP problem. By exploiting the unique structure of the original built model, a mixed-integer convex programming model is subsequently developed. An effective global optimization method with several outer-approximation schemes is put up to find the global optimal or e-optimal solution to the EVFS&TP problem. A case study based on a one-way carsharing operator in Singapore is conducted to demonstrate the efficiency of the proposed model and solution method and further analyse the impact of demand, the degree of demand variation, the fixed operational cost of the vehicles as well as payment for personnel on the performance of the one-way carsharing services.

Electric vehicle fleet size and trip pricing for one-way carsharing services considering vehicle relocation and personnel assignment

Carsharing and sustainable travel behavior: Results from the San Francisco Bay Area

A solution to the imbalance of vehicles in one-way carsharing systems is vehicle relocation which involves staff members to redistribute the vehicles between stations. Vehicle relocation, however, can lead to an imbalance of staff members between stations. Thus, staff members, themselves, need to be relocated between stations to perform the vehicle relocations. This study addresses the joint optimization of vehicle relocation and staff rebalancing using two integrated multi-traveling salesman formulations. Results show that fleet size is more sensitive to demand than staff size, staff size is inversely related to vehicle cost, and that vehicle relocation time increases with vehicle cost.

Vehicle relocation and staff rebalancing in one-way carsharing systems

The recent acquisitions of IGO CarSharing by Enterprise Holdings in May 2013 and Zipcar by the Avis Budget Group in January 2013 continues a trend of mergers and acquisitions in North American “classic” carsharing (or roundtrip, short-term vehicle access). This trend began in the early 2000s with the Flexcar acquisition of CarSharing Portland in 2001 and the merger of Zipcar and Flexcar in 2007. Mergers and acquisitions again became an industry hallmark with the Enterprise Holdings’ acquisition of PhillyCarShare in 2011 and their acquisition of Mint Cars On-Demand in 2012.

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Innovative Mobility: Carsharing Outlook

Increasingly, transportation planners and managers, at all levels of government, are recognizing the profound impact that transportation systems, availability, and access have on quality of life, economic well-being, and social equity. For many Departments of Transportation (DOTs), shifting their planning, evaluation, and procurement criteria to better reflect social and economic goals is a significant departure from decades of planning and management for vehicle throughput, with indicators such as level of service (LOS) and congestion. The California Department of Transportation (Caltrans) has embraced this broader understanding of transportation in their 2015-2020 Strategic Management Plan. Goal 3 of the Plan, “Sustainability, Livability and Economy”, tasks Caltrans to better align State decisions with sustainability goals and objectives. Specifically, Caltrans is to develop separate prosperity, accessibility, and livability scores that will be integrated into the decision-making process for priorities and project development. The Transportation Sustainability Research Center at UC Berkeley conducted a series of tasks to assist Caltrans with an understanding of prosperity, accessibility, and livability metrics. Research findings were collected through a combination of literature reviews and expert interviews. Researchers found that prosperity, accessibility, and livability metrics all involve a component of cooperation with partner jurisdictions. A flexible approach that accounts for local and corridor considerations and evolves over time is emphasized. The white paper highlights the importance of equity considerations, data availability, and the scale of measurement. Prosperity emphasizes long-term or short-term strategies to improve quality of life, focusing on economic indicators, such as income, business, and property values. Prosperity metrics can be used to prioritize transportation projects based on social, environmental, or equity concerns. Accessibility metrics reflect the ability for transportation systems to provide people with access to opportunities. Metrics are centered on travel time and length, land use, mobility, and the availability of public transit. Livability focuses on quality of life improvements with community outcomes and impacts at the local level. Metrics—such as affordability, public health, quality of accessibility, environment, aesthetics, and public participation—all pertain to livability.

https://rosap.ntl.bts.gov/view/dot/37223/dot_37223_DS1.pdf

Mark Jaffee

Papers

Innovative Mobility: Carsharing Outlook

Moving Toward a Sustainable California : Exploring Livability, Accessibility & Prosperity