  We present a near-linear time approximation algorithm for the subtrajectory
cluster problem of $c$-packed trajectories. The problem involves finding $m$
subtrajectories within a given trajectory $T$ such that their Fr\'echet
distances are at most $(1 + \varepsilon)d$, and at least one subtrajectory must
be of length~$l$ or longer. A trajectory $T$ is $c$-packed if the intersection
of $T$ and any ball $B$ with radius $r$ is at most $c \cdot r$ in length.
  Previous results by Gudmundsson and Wong
\cite{GudmundssonWong2022Cubicupperlower} established an $\Omega(n^3)$ lower
bound unless the Strong Exponential Time Hypothesis fails, and they presented
an $O(n^3 \log^2 n)$ time algorithm. We circumvent this conditional lower bound
by studying subtrajectory cluster on $c$-packed trajectories, resulting in an
algorithm with an $O((c^2
n/\varepsilon^2)\log(c/\varepsilon)\log(n/\varepsilon))$ time complexity.
