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Today's railway signalling system heavily relies on trackside infrastructuresuch as axle counters and track balises. This system has proven itself to bereliable, however, it is not very efficient and, moreover, very costly. Thus,it is not suited to overcome the future challenges in railway transportation.For this reason, signalling systems based on train-borne sensors have gainedinterest recently. In this context, train-borne localization is one of the mainresearch challenges. So far there is no sensor set-up which meets the demandingrequirements for a localization system, both in the sense of accuracy as wellas safety. To help overcome these issues in the near future we present ourlatest research results here. Earlier we published a localization algorithmwhich is characterized by an increased accuracy in cross-track directioncompared to a standard Kalman filter (KF) approach, as has been shown insimulations [1]. To verify these results practically, we recorded data from aGlobal Navigation Satellite System (GNSS) and an inertial measurement unit(IMU) on a test drive. The localization accuracy is evaluated with the help ofOpenStreetMap (OSM) data and site plans. Furthermore, we evaluate the qualityof the estimated geometric track-map, which is additionally provided in theprocess of the localization algorithm [2]. We conclude with some remarks on theresearch challenges towards train-borne localization and suggest further stepsto overcome them.

Train-borne Localization Exploiting Track-Geometry Constraints -- A Practical Evaluation