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This work presents an estimation strategy that provides a good localization and a highly accurate measurement of the distance run by a public transportation vehicle. To this aim, the vehicle is equipped with a global positioning system (GPS) sensor, to retrieve the geographical position, a wheel speed sensor, to measure the vehicle velocity, and a gyroscope, to measure the yaw velocity. A model-based hybrid procedure has been proposed, based on the GPS signal reliability, guaranteeing robustness for temporary loss of satellite signal. In particular, the algorithm switches between a Kalman filter strategy, when the GPS is available, and an open-loop model-based estimation, when it is not available. The algorithm has been tested both in simulation and experimentally and the results are analyzed. In particular, a prototype has been realized to test the strategy on urban and extra urban circuits in Benevento (Italy). The experiments are conducted on a Lancia Kappa 2.0 vehicle, by means of a dSpace MicroAutoBox electronic control unit.

The subthalamic nucleus (STN) plays a central role in movement actuation and manifestation of movement disorders (i.e., tremor, rigidity, akynesia and postural instability) in Parkinson's disease (PD) patients. Moreover, it has been recently revealed that an opportune electrical stimulation of the STN, called deep brain stimulation (DBS), can strongly contribute to the annihilation of the PD-related motor disorders. Currently, a great effort is made both in Medicine, Neurosciences and Engineering for understanding and modeling in details how the STN works, how PD determines its pathological behavior and DBS restores the correct motor function. The paper is organized in two parts. Firstly some stochastic properties of the STN electrical activity are obtained by analyzing a preliminary set of experimental data coming from microelectrode recordings (MERs) in two PD patients who underwent the surgical implantation of DBS electrodes. Then, a nonlinear, stochastic, continuous-state model describing the global electrical behavior of the STN in PD patients is proposed. It is inspired by the fundamental physiologic features of the subthalamic cells and a fictitious vector state is introduced to represent the main dynamics. Its numerical parameters and stochastic properties are chosen by fitting the available data.