A. Partusch,G. Navratil, H. Fiby:

"A Framework to Determine the Spatial Variation of the Optimal Path";

Talk: GI_Forum 2014, Salzburg; 2014-07-01 - 2014-07-04; in: "GI_Forum 2014 Geospatial Innovation for Society", R. Vogler, A. Car, J. Strobl, G. Griesebner (ed.); Wichmann, Berlin (2014), ISBN: 978-3-87907-545-4; 155 - 164.

Optimal paths in networks are determined by costs attached to nodes and edges. However, these costs are uncertain. The question raised in this paper is, how to determine the effect that this uncertainty has on the optimal path, i.e., the spatial distribution of the optimal path. The method used is Monte Carlo Simulation. The simulation was done for the road network of Vienna. Travel time serves a cost function and the temporal distribution of travel time is derived from floating car data. The experiment shows that typically several different paths are possible with similar travel times.

Optimal paths in networks are determined by costs attached to nodes and edges. However, these costs are uncertain. The question raised in this paper is, how to determine the effect that this uncertainty has on the optimal path, i.e., the spatial distribution of the optimal path. The method used is Monte Carlo Simulation. The simulation was done for the road network of Vienna. Travel time serves a cost function and the temporal distribution of travel time is derived from floating car data. The experiment shows that typically several different paths are possible with similar travel times.

Optimal Path, Monte Carlo Simulation, Uncertainty, Floating Car Data

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