一种降低漏报站台区域列车障碍物的自主感知方法和系统
By using lidar and onboard ATC equipment in the rail transit platform area in combination with SLAM algorithm for train positioning and safety margin design, dangerous obstacles in the train travel area are identified, which solves the problem of high false alarm rate of obstacle autonomous perception system in rail transit and improves the system's safety and response speed.
CN117885783BActive Publication Date: 2026-07-17CASCO SIGNAL LTD
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- CASCO SIGNAL LTD
- Filing Date
- 2023-12-05
- Publication Date
- 2026-07-17
AI Technical Summary
Technical Problem
Existing technologies in rail transit station areas have a high rate of false alarms in train obstacle autonomous perception systems, which are difficult to reduce effectively and affect train operation safety.
Method used
Train positioning is achieved by combining LiDAR and onboard ATC equipment with SLAM algorithm. Through safety verification and safety margin design, dangerous obstacles in the train's travel area are identified. Clustering algorithm is used to identify obstacles, and key threshold parameters are set to reduce the false alarm rate.
Benefits of technology
This improved the safety of the train obstacle autonomous perception system, reduced the false alarm rate and the missed alarm rate, shortened the response time, and ensured train operation safety.
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Figure CN117885783B_ABST
Abstract
本发明涉及一种降低漏报站台区域列车障碍物的自主感知方法和系统，该方法基于激光雷达和车载ATC设备的数据作为输入，通过SLAM算法处理激光雷达点云实现列车定位，并加载列车当前位置前方的离线地图实现列车行进区刻画，最后使用聚类算法识别列车行进区内的危险障碍物，所述方法包括下列步骤：步骤S1，列车行进区刻画包括安全验证过程；步骤S2，列车行进区刻画包括安全裕度行进区识别过程；步骤S3，列车行进区内的危险障碍物包括安全裕度识别过程。与现有技术相比，本发明具有降低漏报、控制误报率、更快反应危险障碍物，提高系统安全性等优点。
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