Research on lidar target detection for metro scene
Aiming at the problems of difficult real-time construction of train running forward boundary and complex cluster detection of unstructured track and road environment targets, a lidar based on target detection and forward boundary real-time construction system was proposed. Firstly, the strategy of s...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Electric Drive for Locomotives
2022-03-01
|
| Series: | 机车电传动 |
| Subjects: | |
| Online Access: | http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128X.2022.02.013 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850142692413014016 |
|---|---|
| author | PAN Wenbo LI Cheng YUAN Xiwen LONG Teng ZENG Xiang XIE Guotao |
| author_facet | PAN Wenbo LI Cheng YUAN Xiwen LONG Teng ZENG Xiang XIE Guotao |
| author_sort | PAN Wenbo |
| collection | DOAJ |
| description | Aiming at the problems of difficult real-time construction of train running forward boundary and complex cluster detection of unstructured track and road environment targets, a lidar based on target detection and forward boundary real-time construction system was proposed. Firstly, the strategy of space for time was adopted to improve the efficiency of rail track extraction, and the rail track was extracted steadily by using the local elevation information, global geometric parallel information and multi-frame information of the rail track. Then, the forward limit of train passage was constructed based on the extracted rail track position in real time. Secondly, based on the point cloud depth map and gradient and distance characteristics, the obstacle clustering problem in non-paved road scenarios was solved, and the track information was used for multi-target tracking to improve the stability of target tracking. By real train test on metro scene, it was proved that the proposed method could extract track position accurately and reliably, it also could detect and track targets. |
| format | Article |
| id | doaj-art-0acb06e5eaad417481c605c5c94b6d9f |
| institution | OA Journals |
| issn | 1000-128X |
| language | zho |
| publishDate | 2022-03-01 |
| publisher | Editorial Department of Electric Drive for Locomotives |
| record_format | Article |
| series | 机车电传动 |
| spelling | doaj-art-0acb06e5eaad417481c605c5c94b6d9f2025-08-20T02:28:59ZzhoEditorial Department of Electric Drive for Locomotives机车电传动1000-128X2022-03-01899626163796Research on lidar target detection for metro scenePAN WenboLI ChengYUAN XiwenLONG TengZENG XiangXIE GuotaoAiming at the problems of difficult real-time construction of train running forward boundary and complex cluster detection of unstructured track and road environment targets, a lidar based on target detection and forward boundary real-time construction system was proposed. Firstly, the strategy of space for time was adopted to improve the efficiency of rail track extraction, and the rail track was extracted steadily by using the local elevation information, global geometric parallel information and multi-frame information of the rail track. Then, the forward limit of train passage was constructed based on the extracted rail track position in real time. Secondly, based on the point cloud depth map and gradient and distance characteristics, the obstacle clustering problem in non-paved road scenarios was solved, and the track information was used for multi-target tracking to improve the stability of target tracking. By real train test on metro scene, it was proved that the proposed method could extract track position accurately and reliably, it also could detect and track targets.http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128X.2022.02.013metro trainslidartrack extractionsegmentation and clusteringtarget detectionurban rail transit |
| spellingShingle | PAN Wenbo LI Cheng YUAN Xiwen LONG Teng ZENG Xiang XIE Guotao Research on lidar target detection for metro scene 机车电传动 metro trains lidar track extraction segmentation and clustering target detection urban rail transit |
| title | Research on lidar target detection for metro scene |
| title_full | Research on lidar target detection for metro scene |
| title_fullStr | Research on lidar target detection for metro scene |
| title_full_unstemmed | Research on lidar target detection for metro scene |
| title_short | Research on lidar target detection for metro scene |
| title_sort | research on lidar target detection for metro scene |
| topic | metro trains lidar track extraction segmentation and clustering target detection urban rail transit |
| url | http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128X.2022.02.013 |
| work_keys_str_mv | AT panwenbo researchonlidartargetdetectionformetroscene AT licheng researchonlidartargetdetectionformetroscene AT yuanxiwen researchonlidartargetdetectionformetroscene AT longteng researchonlidartargetdetectionformetroscene AT zengxiang researchonlidartargetdetectionformetroscene AT xieguotao researchonlidartargetdetectionformetroscene |