Capacity and information issues in electric vehicle charging stations with strategic customers

In queueing systems with strategic customers, information and travel are critical but often separate areas of study. Information allows customers to make better decisions, while the need to travel to a physical location imposes costs that influence those decisions. This thesis develops a unified framework to analyze a queueing system that incorporates both of these features: customer information asymmetry and a required travel process. We model a single-server system where a fraction of customers can observe the queue length before traveling, while others remain uninformed. This structure is particularly relevant to EV charging stations, where drivers value information about congestion to avoid costly wasted trips. We construct a tandem queueing model, prove the existence of a symmetric equilibrium, and develop a numerical algorithm to solve for the equilibrium strategies. Our analysis of the results shows how a service provider can use an information fee not only as a source of revenue but also as a strategic tool to control the level of public information and optimize system-wide performance metrics like throughput and social welfare. The findings provide several key managerial insights for charging station planning and operation.