Although electric vehicles are attracting increasing interest from consumers and automakers, the disadvantages associated with limited range and the current scarcity of public recharge stations have played a key role in limiting their large scale adoption. In this paper, we explore how information technologies might be used to mitigate `range anxiety' and further strengthen the potential of electric vehicle integration with the renewable energy generation and storage. We motivate several mobile applications/services which would improve the ownership experience of electric vehicles and flexibility for energy providers. Our work leverages a previously proposed sensor platform for collecting travel-time and energy-usage data for a road network by a community of electric car drivers. Travel-time and energy-usage on a given road segment may exhibit substantial variability due to environmental and temporal factors, e.g., congestion, road's grade, AC on/off, etc. Such variability in turn, makes it difficult to accurately predict travel-times as well as the feasible range of a car given its current energy reserves. However, by collecting statistical data using cars/mobiles as probes one can quantify such uncertainty and develop complementary algorithms to counter the anxiety and time waste associated with such uncertainty. This paper develops the necessary (routing) algorithms to support these new classes of applications/services for electric vehicles.