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An analysis of different sensors for turnout detection for train-borne localization systems

机译:用于培训定位系统的路孔检测的不同传感器分析

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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.
机译:安全铁路操作需要在铁路网络中获得可靠的火车定位。因此,本文旨在提高最近提出的列车定位系统的准确性和可靠性。这些方法中的大多数是基于全球导航卫星系统(GNSS)和测量仪。然而,这些系统旨在具有关于准确性和可用性的严重缺点。我们认为,在其上检测到投票和分支方向的能力是最有价值的改进线索。了解分支方向提供有关列车位置的拓扑信息。因此,它以理想的方式补充了GNSS和纵向位置信息的地理信息。利用这种传感器设置,即使GNSS不可用或受到干扰,也可以进行轨道选择性定位。因此,本文比较了不同传感器原理对投灯检测的个性益处,例如惯性测量单元(IMU),相机和LIDAR(光检测和测距)传感器。因此,我们专注于激光器传感器。对于那些我们定义要求,审查市场,并在电车轨道场景中报告案例研究的结果。我们证明可以检测轨道,投票率和平台。最后,我们讨论了我们的研究结果,并对我们的进一步研究进行了展望。

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