A hybrid procedure strategy for vehicle localization system: Design and prototyping

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.