  This paper considers an electric vehicle charging scheduling setting where
vehicle users can reserve charging time in advance at a charging station. In
this setting, users are allowed to explicitly express their preferences over
different start times and the length of charging periods for charging their
vehicles. The goal is to compute optimal charging schedules which maximize the
social welfare of all users given their time preferences and the state of
charge of their vehicles. Assuming that users are self-interested agents who
may behave strategically to advance their own benefits rather than the social
welfare of all agents, we propose an iterative auction which computes high
quality schedules and, at the same time, preserve users' privacy by
progressively eliciting their preferences as necessary. We conduct a game
theoretical analysis on the proposed iterative auction to prove its individual
rationality and the best response for agents. Through extensive experiments, we
demonstrate that the iterative auction can achieve high-efficiency solutions
with a partial value information. Additionally, we explore the relationship
between scheduling efficiency and information revelation in the auction.
