  Let $\mathcal{P}$ be a set of $h$ pairwise-disjoint polygonal obstacles with
a total of $n$ vertices in the plane. We consider the problem of building a
data structure that can quickly compute an $L_1$ shortest obstacle-avoiding
path between any two query points $s$ and $t$. Previously, a data structure of
size $O(n^2\log n)$ was constructed in $O(n^2\log^2 n)$ time that answers each
two-point query in $O(\log^2 n+k)$ time, i.e., the shortest path length is
reported in $O(\log^2 n)$ time and an actual path is reported in additional
$O(k)$ time, where $k$ is the number of edges of the output path. In this
paper, we build a new data structure of size $O(n+h^2\cdot \log h \cdot
4^{\sqrt{\log h}})$ in $O(n+h^2\cdot \log^{2} h \cdot 4^{\sqrt{\log h}})$ time
that answers each query in $O(\log n+k)$ time. Note that $n+h^2\cdot \log^{2} h
\cdot 4^{\sqrt{\log h}}=O(n+h^{2+\epsilon})$ for any constant $\epsilon>0$.
Further, we extend our techniques to the weighted rectilinear version in which
the "obstacles" of $\mathcal{P}$ are rectilinear regions with "weights" and
allow $L_1$ paths to travel through them with weighted costs. Our algorithm
answers each query in $O(\log n+k)$ time with a data structure of size
$O(n^2\cdot \log n\cdot 4^{\sqrt{\log n}})$ that is built in $O(n^2\cdot
\log^{2} n\cdot 4^{\sqrt{\log n}})$ time (note that $n^2\cdot \log^{2} n\cdot
4^{\sqrt{\log n}}= O(n^{2+\epsilon})$ for any constant $\epsilon>0$).
