Safe railway operation requires a reliable localization of trains in the railway network. Hence, this paper aims to improve the accuracy and reliability of train-borne localization systems proposed recently. Most of these approaches are based on a global navigation satellite system (GNSS) and odometers. However, these systems turned out to have severe shortcomings concerning accuracy and availability. We believe that the ability to detect turnouts and the branching direction thereon is the most valuable clue for improvement. Knowing the branching direction provides topological information about the train position. Thus, it complements the geographical information of GNSS and the longitudinal position information of odometers in an ideal way. With such a sensor setup a track-selective localization would be possible even if GNSS is unavailable or disturbed. Therefore, this paper compares the individual benefits of different sensor principles for turnout detection such as inertial measurement units (IMUs), cameras, and lidar (light detection and ranging) sensors. As a consequence, we focus on lidar sensors. For those we define requirements, review the market, and report the results of a case study in a tramway scenario. We proved that it is possible to detect rails, turnouts, and platforms. Finally we discuss our findings intensively and give an outlook on our further research.
This article investigates in which way a lidar sensor can be used in a train-borne localization system. The idea is to sense infrastructure elements like rails and turnouts with the lidar sensor and to recognize those objects with a template-matching approach. A requirement analysis for the lidar sensor is presented and a market review based on these requirements is performed. Furthermore, an approach for template matching on lidar scans to recognize infrastructure objects is introduced and its empirical performance is demonstrated based on measurements taken in a light rail environment. The overall goal of the integration of lidar sensors is to fill the sensory gap of existing train localization approaches, which are able to determine the exact, track-selective train position only if highly accurate position measurements from satellite navigation systems are available, which is often not the case. By integrating a lidar sensor, the localization system becomes more diverse, more robust, and can tolerate missing or faulty measurements from the satellite navigation system.
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