minor changes

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2016-02-17 21:46:01 +01:00
parent 9db832d6b4
commit b79b3746c0

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@@ -91,17 +91,18 @@
$u,v$, examined by the shortest-path algorithm.
To downvote vertices near walls, we need to determine the distance of each vertex from its nearest wall.
We therefore derive an inverted version $G' = (V', E')$ of the graph $G$, just describing walls and other
obstacles. A nearest-neighbour search \cite{Cover1967} within $V'$ provides the vertex $v'$
nearest to $v$:
\begin{equation}
v' = \fNN{v}{V'} \enskip .
\end{equation}
We therefore derive an inverted version $G' = (V', E')$ of the graph $G$, just describing walls and
obstacles. A nearest-neighbour search \cite{Cover1967} $\fNN{v}{V'}$ within $V'$ provides the vertex
nearest to $v$.
%\begin{equation}
% v' = \fNN{v}{V'} \enskip .
%\end{equation}
To get a smooth gradient around walls, the avoidance-factor
is derived using a normal distribution with a deviation of \SI{0.5}{\meter}:
%
\begin{equation}
\fWA{v} = \mathcal{N}( \fDistance{v}{\fNN{v}{V'}} \mid 0.0, 0.5^2) \\
\fWA{v} = \mathcal{N}( \| v - \fNN{v}{V'} \| \mid 0.0, 0.5^2)
\enskip .
\label{eq:wallAvoidance}
\end{equation}
%
@@ -195,10 +196,11 @@
Hereafter, every node in the grid knows the distance and shortest path to the pedestrian's target.
To get realistic path suggestions, we use the importance-factors to adjust the edge-weight
$\delta(v_1, v_2)$ for the Dijkstra:
$\delta(e_{1,2})$ for the Dijkstra:
%
\begin{equation}
\begin{split}
\delta(e_{1,2}) =
\delta(v_1, v_2) =
\frac
{ \| v_1 - v_2 \| }