列车轨道占用自动识别算法

为解决列车在道岔及平行股道区段的轨道占用自动识别问题, 基于LTS-Hausdorff距离, 结合D-S证据理论, 提出了一种新的列车轨道占用自动识别算法, 建立了可用于列车轨道占用自动识别的轨道LTS-Hausdorff距离参考模板, 分析了LTS-Hausdorff距离的计算过程及轨道占用自动识别决策方法, 研究了列车速度与搜索阈值对自动识别算法的影响。验证结果表明: 在轨迹点数量为10时, 该识别算法和基于最大似然准则的轨道识别决策的识别结果相同; 列车速度越高, 轨迹点越少, 算法仍可进行有效识别; 搜索阈值越小, 算法实现时间越短。可见, 识别算法有效。

Automatic identification algorithm of train track occupancy

In order to resolve the automatic identification problems of train track occupancy at turnouts and on parallel sections, a new automatic identification algorithm was proposed based on LTS-Hausdorff distance and D-S evidence theory. The reference template of track LTS-Hausdorff distance was established, the calculation process of LTS-Hausdorff distance and the decision method of automatic identification were analyzed, and the effects of train speed and search threshold on the algorithm were studied. Test result shows that when there are 10 track points, the results of the new algorithm and the maximum likelihood track identification decision are same. The higher train speed is, the less track points are, and the algorithm is still effective. The smaller search threshold is, the shorter the algorithm realizing time is. So the algorithm is valid.