Future requirements for drastic reduction of CO2 production and energy consumption will lead to significant changes in the way we see mobility in the years to come. However, the automotive industry has identified significant barriers to the adoption of electric vehicles, including reduced driving range and greatly increased refueling times.Automated cars have the potential to reduce the environmental impact of driving, and increase the safety of motor vehicle travel. The current state-of-the-art in vehicle automation requires a suite of expensive sensors. While the cost of these sensors is decreasing, integrating them into electric cars will increase the price and represent another barrier to adoption.The V-Charge Project, funded by the European Commission, seeks to address these problems simultaneously by developing an electric automated car, outfitted with close-to-market sensors, which is able to automate valet parking and recharging for integration into a future transportation system. The final goal is the demonstration of a fully operational system including automated navigation and parking. This paper presents an overview of the V-Charge system, from the platform setup to the mapping, perception, and planning sub-systems.
Electric vehicles (EVs) still have relatively long and frequent charging cycles. Moreover, charging resources are typically limited and must therefore be used efficiently. The V-Charge project has the vision to provide a solution by combining autonomous valet parking with e-mobility, introducing improved parking and charging comfort. V-Charge proposes a solution for charging autonomous EVs in parking places and efficiently using scarce charging resources, thus simplifying the life of the customer and increasing the feasibility of EVs. For the management of parking lots and charging resources, V-Charge provides a server back end and a communication infrastructure. In this paper, we present our design of scheduling concepts for a coordinated charging strategy that is implemented by this back end. Through intensive simulations, we show that the V-Charge server is able to efficiently handle realistic parking volume and performs well in fulfilling customer requirements, e.g., energy demand for the next driving tasks. Moreover, we evaluate the suitability of various scheduling strategies in different usage scenarios. For the simulation setup, real-world parking statistics obtained from Hamburg Airport and the City of Braunschweig, Germany, are used.
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