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The use of carsharing vehicles over a period of 16 months in 2006-07 was compared to built environment and demographic factors in this GIS-based multivariate regression study of an urban U.S. carsharing operator. Carsharing is a relatively new transportation industry in which companies provide members with short-term vehicle access from distributed neighborhood locations. The number of registered carsharing members in North America has doubled every year or two to a current level of approximately 320,000. Researchers have long supposed that public transit access is a key factor driving demand for carsharing. The results of this study, however, find an ambiguous relationship between the activity at carsharing locations and public transit access. Light rail availability is found to have a significant and positive relationship to carsharing demand. Regional rail availability is found to be weakly and negatively associated with carsharing demand, although limitations in the available data make it impossible to ascribe the observed difference to user demand, random variation, or other factors specific to the industry.

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The Energy Information Administration estimates that, in 2007, U.S. domestic passenger vehicles burned 113 billion gallons of fuel and thus generated more than 16% of U.S. greenhouse gas emissions. Past field experiments and simulations suggest that energy information feedback to drivers could have spared 10% to 25% of those gallons. However, the theoretical underpinnings of past experiments have primarily been ad hoc, with application of their results limited to specific conditions of the experiment and feedback design. More rigorous behavioral theory would allow researchers to account for more variation in driver response to feedback, create testable hypotheses about the effectiveness of current systems, and provide a basis for designing more-effective systems. This paper presents drivers’ responses to energy feedback in a field test involving 98 participants from 43 households in California and compares the results with the concepts that underlie the theory of planned behavior and the extended model of goal-directed behavior. About 40% of participants reported more economical driving behaviors after viewing the feedback; estimation of actual changes in fuel use is left for future research. After viewing real-time energy information, numerous drivers reported setting goals, having emotional reactions, and creating new driving behaviors. Distraction from the primary driving task was a persistent problem for some drivers. Web-accessible information was not as motivating to participants. Finally, the study finds evidence of correspondence between theoretical behavioral factors and drivers’ responses.

Mobile device applications (apps) are becoming an important source of information, control, and motivation for EV drivers. Here we review the current ecosystem of mobile applications that are available for EV drivers and consumers and find that apps are available in six basic categories: purchase decisions, vehicle dashboards, charging availability and payment, smart grid interaction, route planning, and driver competitions. The current range of the EVspecific mobile marketplace extends from pre-sale consumer information, charging information and control, and EV specific navigation features among other services. However, the market is highly fragmented, with applications providing niche information, and using various methodologies. In addition, we find that the barriers to more useful apps are a lack of vehicle and charger APIs (application programming interfaces), lack of data availability, reliability, format and types, and proprietary payment and billing methods. We conclude that mobile applications for EVs are a growing market that provide important direct benefits as well as ancillary services to EV owners, although the lack of uniformity and standards between both vehicle and charger systems is a serious barrier to the broader use of mobile applications for EVs.