  We study the quality of weighted shortest paths when a continuous
2-dimensional space is discretized by a weighted triangular tessellation. In
order to evaluate how well the tessellation approximates the 2-dimensional
space, we study three types of shortest paths: a weighted shortest path~$
\mathit{SP_w}(s,t) $, which is a shortest path from $ s $ to $ t $ in the
space; a weighted shortest vertex path $ \mathit{SVP_w}(s,t) $, which is a
shortest path where the vertices of the path are vertices of the tessellation;
and a weighted shortest grid path~$ \mathit{SGP_w}(s,t) $, which is a shortest
path whose edges are edges of the tessellation. The ratios $ \frac{\lVert
\mathit{SGP_w}(s,t)\rVert}{\lVert \mathit{SP_w}(s,t)\rVert} $, $ \frac{\lVert
\mathit{SVP_w}(s,t)\rVert}{\lVert \mathit{SP_w}(s,t)\rVert} $, $ \frac{\lVert
\mathit{SGP_w}(s,t)\rVert}{\lVert \mathit{SVP_w}(s,t)\rVert} $ provide
estimates on the quality of the approximation.
  Given any arbitrary weight assignment to the faces of a triangular
tessellation, we prove upper and lower bounds on the estimates that are
independent of the weight assignment. Our main result is that $ \frac{\lVert
\mathit{SGP_w}(s,t)\rVert}{\lVert \mathit{SP_w}(s,t)\rVert} =
\frac{2}{\sqrt{3}} \approx 1.15 $ in the worst case, and this is tight.
