Intelligent transportation related complex systems and sensors

Building around innovative services related to different modes of transport and traffic management, intelligent transport systems (ITSs) are being widely adopted worldwide to improve the efficiency and safety of the transportation system. They enable users to be better informed and make safer, more coordinated, and smarter decisions on the use of transport networks. Current ITSs are complex systems, made up of several components/sub-systems characterized by time-dependent interactions among themselves. Some examples of these transportation-related complex systems include road traffic sensors, autonomous/automated cars, smart cities, smart sensors, virtual sensors, traffic control systems, smart roads, logistics systems, smart mobility systems, and many others that are emerging from niche areas

Emotion and stress recognition related sensors and machine learning technologies

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Stability analysis and limit cycles of high order sigma-delta modulators

In this chapter we present an unified approach for study the stability and validation of potential limit cycles of one bit high order Sigma-Delta modulators. The approach is general because it uses the general form of a Sigma-Delta modulator. It is based on a parallel decomposition of the modulator and a direct nonlinear systems analysis. In this representation, the general N-th order modulator is transformed into a decomposition of low order, generally complex modulators, which interact only through the quantizer function. The developed conditions for stability and for validation of potential limit cycles are very easy for implementation and this procedure is very fast

Synchronization of movement for a large-scale crowd

Real world models of large-scale crowd movement lead to computationally intractable problems implied by various classes of non-linear stochastic differential equations. Recently, cellular automata (CA) have been successfully applied to model the dynamics of vehicular traffic, ants and pedestrians’ crowd movement and evacuation without taking into account mental properties. In this paper we study a large-scale crowd movement based on a CA approach and evaluated by the following three criteria: the minimization of evacuation time, maximization of instantaneous flow of pedestrians, and maximization of mentality-based synchronization of a crowd. Our computational experiments show that there exist interdependencies between the three criteria