New algorithms for the simplification of multiple trajectories under bandwidth constraints

Gilles Dejaegere, Mahmoud Sakr
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Abstract

This study introduces time-windowed variations of three established trajectory simplification algorithms. These new algorithms are specifically designed to be used in contexts with bandwidth limitations. We present the details of these algorithms and highlight the differences compared to their classical counterparts. To evaluate their performance, we conduct accuracy assessments for varying sizes of time windows, utilizing two different datasets and exploring different compression ratios. The accuracies of the proposed algorithms are compared with those of existing methods. Our findings demonstrate that, for larger time windows, the enhanced version of the bandwidth-constrained STTrace outperforms other algorithms, with the bandwidth-constrained improved version of \squish also yielding satisfactory results at a lower computational cost. Conversely, for short time windows, only the bandwidth-constrained version of Dead Reckoning remains satisfactory.
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带宽限制下简化多轨迹的新算法
本研究介绍了三种既定轨迹简化算法的时间窗口变体。这些新算法专门设计用于带宽受限的情况。我们介绍了这些算法的细节,并强调了与经典算法的不同之处。为了评估这些算法的性能,我们利用两个不同的数据集和不同的压缩比,对不同大小的时间窗口进行了精度评估。建议算法的准确度与现有方法的准确度进行了比较。我们的研究结果表明,对于较大的时间窗口,带宽受限的 STTrace 增强版优于其他算法,而带宽受限的 \squish 改进版也能以较低的计算成本获得令人满意的结果。相反,对于短时间窗口,只有带宽受限的 DeadReckoning 版本仍然令人满意。
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