Assessing the Potential Extent of Carsharing: A New Method and Its Implications

Members of carsharing organizations reduce both the number of vehicles owned and vehicle miles traveled (VMT). Given these benefits at the individual level, carsharing may interest policy makers as another tool to address the negative environmental, economic, and social consequences of automobile dependence. However, the aggregate effects of carsharing must be estimated before sound policy decisions can be made. This paper describes a Monte Carlo simulation of the economic decision to own or share a vehicle on the basis of major cost components and past vehicle use. The simulation estimates the percentage of vehicles that would be cheaper to share than own. In Baltimore, Maryland, this result ranged from 4.2% under a traditional neighborhood carsharing model to 14.8% in a commuter-based carsharing model. Sensitivity analyses identified travel time and VMT as the most important economic factors, which likely incorporate other factors such as transit access and environmental attitudes. Because travel behavior, not ownership cost, drives the economic carsharing decision, the model hypothesizes that there will be increasing marginal societal benefits from policies that promote carsharing. The model can be applied to any geographic area and can be used to assess carsharing impacts of various policies that change the economics of owning or driving an auto. These results indicate that carsharing can become prevalent enough to be considered an important policy tool