In this work we present a SPICE-based RTL subthresholdleakage model analyzing components built in 70nm technology [1]. We present a separation approach regarding interand intra-die threshold variations, temperature, supply-voltage, and state dependence. The body-effect and differences between NMOS and PMOS introduce a leakage state dependence of one order of magnitude [2,3]. We show that the leakage of RT-components still shows state dependencies between 20% and 80%. A leakage model not regarding the state can never be more accurate than this. The proposed state aware model has an average error of 6.7% for the RT-components analyzed.

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In this paper, we propose an approach how connected and highly automated vehicles can perform cooperative maneuvers such as lane changes and left-turns at urban intersections where they have to deal with humanoperated vehicles and vulnerable road users such as cyclists and pedestrians in so-called mixed traffic. In order to support cooperative maneuvers the urban intersection is equipped with an intelligent controller which has access to different sensors along the intersection to detect and predict the behavior of the traffic participants involved. Since the intersection controller cannot directly control all road users and -not least due to the legal situation -driving decisions must always be made by the vehicle controller itself, we focus on a decentralized control paradigm. In this context, connected and highly automated vehicles use some carefully selected game theory concepts to make the best possible and clear decisions about cooperative maneuvers. The aim is to improve traffic efficiency while maintaining road safety at the same time. Our first results obtained with a prototypical implementation of the approach in a traffic simulation are promising.

Abstract. The approach proposed in this paper forms the front-end of a framework for the complete design flow from specification models of new automotive functions captured in Matlab Simulink to their distributed execution on hierarchical bus-based electronic architectures hosting the release of already deployed automotive functions. The process starts by deriving a task structure from a given Matlab Simulink model. Because the obtained network is typically unbalanced in the sense of computational node weights, nodes are melted following an optimization metric called cohesion where nodes are attracted by high communication density and repelled by high node weights. This reduces task-switching times by avoiding too lightweight tasks and relieves the bus by keeping inter-task communication low. This so-called Task Creation encloses the translation of the synchronous block diagram model of Simulink into a message-based task network formalism that serves as semantic base.

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