Secure, Resilient, and Safety Critical Architecture of Charging Stations for Unsupervised Autonomous Vehicles

The anticipated wide-spread deployment of unsupervised Autonomous Vehicles (AVs) across the globe will reshape the existing vehicle-related services (e.g., refueling/charging, parking, car washing, etc.) into new forms. Especially, a new paradigm of the refueling/charging mechanism can offer new economies and service opportunities. It has the potential to make a great impact on the current gasoline station industry given its enormous market size (e.g., annual sales more than $418 billion in 2016), as the AVs become mainstream modes of transportation. We propose a resilient and secure layered architecture of completely automated charging/refueling stations for unsupervised AVs. To demonstrate the feasibility of the architecture, we develop an analytical framework using a bottom-up approach. Then, we demonstrate the operation of a charging station as an essential component of the proposed architecture. The main goal of charging station's operation is to optimize scheduling of electric vehicles for their charging service. A divide-and-conquer strategy is employed for such scheduling optimization at the operational level real-time decision-making. In this optimization, the objective function is to minimize the sum of charging completion times of all vehicles in the queue. A mixed-integer linear programming model is considered to solve this online optimal scheduling procedure. An illustrative example of the scheduling solution that is obtained by a Matlab code combined with the Gurobi optimization solver is presented.