Biblio

Since the late 1990s the sales of processors targeted for embedded systems has exceeded sales for the PC market. Some embedded systems tightly link the computing resources to the physical world. Such systems are called cyber-physical systems. Autonomous cyber-physical systems often have safety-critical missions, which means they must be fault tolerant. Unfortunately fault recovery options are limited; adapting the physical system behavior may be the only viable option. Consequently, autonomous cyber-physical systems are a class of adaptive systems. The evolvable hardware field has developed a number of techniques that should prove to be useful for designing cyber-physical systems although work along those lines has only recently begun. In this paper we provide an overview of cyber-physical systems and then describe how two evolvable hardware techniques can be used to adapt the physical system behavior in real-time. The goal is to introduce cyber-physical systems to the evolvable hardware community and encourage those researchers to begin working in this emerging field.

We propose a macroscopic traffic network flow model suitable for analysis as a dynamical system, and we qualitatively analyze equilibrium flows as well as convergence. Flows at a junction are determined by downstream supply of capacity as well as upstream demand of traffic wishing to flow through the junction. This approach is rooted in the celebrated Cell Transmission Model for freeway traffic flow. Unlike related results which rely on certain system cooperativity properties, our model generally does not possess these properties. We show that the lack of cooperativity is in fact a useful feature that allows traffic control methods, such as ramp metering, to be effective. Finally, we leverage the results of the technical note to develop a linear program for optimal ramp metering.