一种基于改进LCSS的相似轨迹提取方法

A Similar Trajectory Extraction Method Based on Improved LCSS

  • 摘要: 随着智能交通和高级驾驶辅助系统的火热发展,如何根据车辆轨迹数据生成高精地图成为业界的一大难题。轨迹相似性计算与相似轨迹提取是利用相似轨迹推理剩余车道位置的重要步骤,其正确率极大地影响车道位置的精度。传统最长公共子序列(longest common subsequence,LCSS)算法多用于计算重叠轨迹的相似性,针对此问题,根据采集的车道轨迹互相平行且保持固定距离的特点,提出一种适用于提取此类相似轨迹的改进LCSS方法。首先构建缓冲区,筛选可能相似的轨迹,然后利用基于平移和重采样的轨迹对齐策略使两条轨迹在时空中同步,最后基于LCSS计算两条轨迹的相似性,当相似度满足阈值条件时,判定该轨迹对相似。对比实验表明该方法能有效地提取相似轨迹。

     

    Abstract: With the rapid development of intelligent transportation, how to generate high-precision maps based on vehicle trajectory data has become a major problem in the industry. Trajectory similarity calculation and similar trajectory extraction are important steps to use the similar trajectory to infer the remaining lane position, and its correction greatly affects the accuracy of the lane position. The traditional LCSS (longest common subsequence) algorithm is mostly used to calculate the similarity of overlapping trajectories. To solve this problem, according to the characteristics that the lane trajectories are parallel and maintain a fixed distance, an improved LCSS method is proposed. Firstly, the buffer is constructed to screen out similar trajectories, then the trajectory alignment strategy based on translation and resampling is used to synchronize the two trajectories in space and time. Finally, the similarity of the two trajectories is calculated based on LCSS. When the similarity satisfies the threshold condition, it is determined that the trajectory pairs are similar. Experiment results show that the proposed method can effectively extract similar trajectories.

     

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