A localization algorithm for railway vehicles

Abstract

Odometry is a safety on-board subsystem of modern railway Automatic Train Protection (ATP) and Automatic Train Control (ATC) and his main task is the estimation of instantaneous speed and the travelled distance of the railway vehicle. An accurate estimation is mandatory, because an error (residual) on the train position may lead to a dangerous overestimation of the distance available for braking. To improve the odometry estimate accuracy, the proposed algorithm exploits data fusion of different inputs coming from a redundant sensor layout: in particular, the proposed strategy consists of a sensor fusion between the information coming from a tachometer and an IMU (Inertial Measurements Unit) is carried out. A 3D multibody model has been designed so at to simulate the sensor outputs. Within the framework of the presented research, a custom IMU, designed by ECM S.p.a. has been built. The IMU board is then tested via a dedicated HIL test rig (Hardware in the Loop) that includes an industrial robot able to reproduce the motion of the railway vehicle. The performances of the innovative localization algorithm have been evaluated by generating the experimental outputs. The main aim of this work is the development of an innovative localization algorithm for railway vehicles able to enhance the speed and position estimation accuracy of the classical odometry algorithms, such as the Italian SCMT (Sistema Controllo Marcia Treno). The results highlight a good improvement of the position and speed estimation performances compared to those obtained with classical SCMT algorithms, currently in use on the Italian railway network