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.
Secure, Resilient, and Safety Critical Architecture of Charging Stations for Unsupervised Autonomous Vehicles
01.11.2018
494917 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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