Hardware in the loop (HIL) techniques are widely used for fast prototyping of control systems, electronic and mechatronic devices. In the railway field, several mechatronic on board subsystems are often tested and calibrated following the HIL approach. The accuracy of HIL tests depends on how the simulated virtual environment approximates the physical conditions. As the computational power available on real-time hardware grows, the demand for more complex and realistic models of railway vehicles for real-time application increases. In past research activities, the authors worked on the implementation of simplified real-time models for several applications and in particular for an HIL test rig devoted to the type approval of wheel slide protection systems. The activity has then been focused on the development of a three-dimensional model of the dynamics of a railway vehicle for more complex applications. The paper summarises the features and the results of the study.

The paper summarises the main features concerning the definition of an efficient odometry algorithm to be used in modern automatic train protection and control (ATP/ATC) systems. The availability of a reliable speed and travelled distance estimation is essential for the efficiency and the safety of the whole system. The first essential step in odometric subsystem design is the choice of the sensors, whose output signals will be used for velocity estimation. Then a suitable procedure fusing sensor signals has to be defined as a function of number and type of sensors and accuracy and safety targets. In the paper, the main features of an innovative solution will be summarised and its performance will be presented, in terms of precision in speed and travelled distance estimation.

The analysis of statistical data on work accidents involving forklifts and other industrial vehicles suggests the implementation of sensor-based monitoring and control/supervision systems in order to increase work safety. In fact, drivers' training and proper safety procedures are not sufficient to assure to drastically reduce fatalities and other accidents involving humans. The human factor is responsible for the majority of said accidents: in this context, reliable measurements on machine operation and the surrounding environment together with advanced reasoning and decision-making techniques may reduce the impact of human errors and/or prevent them. Authors have developed in collaboration with the Pramac Group, an international supplier of handling equipments, an innovative control system briefly called in this work active vehicle protection system.