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A novel automatic track identification algorithm based on LTS-Hausdorff distance

机译:基于LTS-Hausdorff距离的新型自动轨迹识别算法

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Train locating information is very important for train control system, how to achieve automatic identification of train track occupancy using GNSS simply in some railway sections without track circuits has been a crucial problem. Hausdorff distance can be used to measure the mismatch between two sets, which is widely used in object matching. This paper presents a novel algorithm for automatic identification of train track occupancy based on LTS-Hausdorff distance and D-S evidence theory. The LTS-Hausdorff distance reference template of railway track was established, the calculation process of LTS-Hausdorff distance and the identify strategy of train track occupancy based on D-S evidence theory were studied. Test results show that the algorithm is efficient and can achieve automatic track identification in low cost.
机译:列车定位信息对于列车控制系统非常重要,如何在一些没有轨道电路的铁路区间内,仅使用GNSS来自动识别列车的轨道占用已成为一个关键问题。 Hausdorff距离可用于测量两个集合之间的不匹配,已广泛用于对象匹配中。本文提出了一种基于LTS-Hausdorff距离和D-S证据理论的自动识别列车轨道占用的算法。建立了铁路轨道LTS-Hausdorff距离参考模板,研究了基于D-S证据理论的LTS-Hausdorff距离的计算过程以及列车轨道占用率的识别策略。测试结果表明,该算法是有效的,并且可以低成本实现自动轨道识别。

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