CLASSIFICATION OF THE ROAD JUNCTIONS BASED ON MULTIPLE
REPRESENTATIONS: ADDING VALUE BY INTRODUCING ALGORITHMIC AND CARTOGRAPHIC
APPROACHES
A.O. Dogru1, N. Van de Weghe2, N.N. Ulugtekin1, P. De Maeyer2
1 - Istanbul Technical University, Cartography Division,
Istanbul, Turkey
2 - Ghent University, Department of Geography, Gent, Belgium
dogruahm@itu.edu.tr
Navigation is one of the fundamental human activities. Thanks to the
technological developments in computer and electronic sciences, navigation has
become an integral part of everyday life. In addition to the technical
components, maps are considered as the basic component of navigation systems.
Moreover, database and visualisation models, which form the basic
infrastructure of these maps, are another fundamental component of these
systems. These maps should be considered in two different dimensions: the base
map data which involve the road network data on which network algorithms, such
as finding shortest path and optimal way, are executed, and the maps which are
used as user interface. Since the display media of the navigation systems are
small in size, it is impossible to present the base map data as such the user
interface during the navigation process. Therefore, multiple representations of
the base maps should be used in navigation processes. These different
representations should be derived from the base map according to the aim, scale
and resolution of the navigation task.
In this study, car navigation is considered as the basic activity and
the multiple representation approach for the production of the navigation maps
is taken into account to derive road network data for different representation
levels of car navigation maps. In this context, road junctions which are the
most complicated elements of the road networks are classified considering two
different approaches, an approach based on cartographic aspects and an approach
based on algorithmic aspects. In the first approach, road junctions are
classified according to their aspects at different representation levels. In
this concept, three representation levels, which are
planned to be derived from 1:5000 scaled base level, are used and
representations of possible road junctions are structured according to
characteristics of these levels. Finally, they are classified by considering
their geometrical shapes in each level. In the second approach, road junctions
are classified according to algorithmic concerns. Junctions are defined
in matrices based on their specific characteristics, and these matrices are
classified according to their similarity. Finally, common representations are
determined for these classes.
As a conclusion, this paper introduces the comparison of the
cartographic and algorithmic approaches for the classification of road
junctions. Since the representation of junctions is the core problem for map
production in terms of multiple representations, this study has a significant
importance from a cartographic point of view with respect to the car navigation
process.