.png){kind=icon}
返回
Anomalous Sub-Trajectory Detection With Graph Contrastive Self-Supervised Learning
.png){kind=icon}
PRE
AI
DOI：10.1109/TVT.2024.3382685.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Some anomalous vehicle trajectories may contain fraudulent behavior or traffic accident information. Existing research mostly starts from a global view, treating the entire trajectory as a detection target to determine whether it is anomalous. However, they failed to fully capture the influence of sub-trajectories on the entire trajectory, thus ignoring some anomalous sub-trajectories. This study proposes an anomalous sub-trajectory detection method (GCSL-ASD) based on graph contrastive self-supervised learning, which identifies anomalous sub-trajectories by mining the supervisory information of trajectory data itself. First, we used map matching to project all historical trajectories onto the road network to achieve more accurate trajectory data representation. Then, to enable the model to transform the detection target from individual trajectory segments to sub-trajectories and thus capture anomalies more accurately, we designed a sub-trajectory aggregation module to aggregate continuous trajectory segments into sub-trajectory. Finally, we used graph convolutional network (GCN) to design the generation module and contrastive learning module to capture sub-trajectory anomalies in attribute space and structure space. We conducted comparative experiments on three real datasets to verify the effectiveness of this method and analyzed the reasons for the driver's local detour behavior.
Keyword:
Anomalous trajectory detection
sub-trajectory
graph convolutional network
graph contrastive self-supervised learning
Anomalous trajectory detection
sub-trajectory
graph convolutional network
graph contrastive self-supervised learning
期刊
IF:
7.1
论文数:
1.8W
被引数:
6.6W
机构
引用论文
Trajectory outlier detection approach based on common slices sub-sequence.png)
APPLIED INTELLIGENCE
APPLIED INTELLIGENCEIF3.5
PREAI
分享收藏
Electrothermal Model for Power LEDs Based on the Equivalent Resistance Concept for LED Driver Design基于LED驱动器设计的等效电阻概念的功率LED电热模型
PREAI
分享收藏
查看更多内容