(HTML) component to dynamically plan or alter
trips; select points of interests and present
information en-route to its users as text or image. It
also possesses a map-based interaction mode. The
architecture for the current version is shown in
Figure 5.
In our current version, the travel assistant gets
live position data (coordinates) either from the
NaviServer, which in turn gets the live data from a
GPS, or interactively by clicking on a map.
NaviServer can also record and read the position
data from a database containing previously recorded
position coordinates. Additionally, the NaviServer
can process the data coming from the ADAS-RP
(Advanced Driver Assistance System – Research
Platform), which is in itself connected to a GPS and
typically provides map data, matched coordinates
and additional information such as road types and
road names.
The travel assistant has a link to POI-information
system to provide the user all the detailed
information regarding POIs selected during the pre-
trip planning. As an output, the travel assistant, en-
route a pre-planned trip, delivers information about
the current position of a vehicle, POI-information
and all the POIs in the vicinity of current position, in
form of POI-view or Map-view or as combination of
both (POI/Map) on a single screen.
5 SUMMARY
The EMODE methodology integrates software
engineering concepts with user interface design
approaches and adopts the model-driven architecture
(MDA) to develop adaptive multimodal interactive
systems. To define platform independent models and
to support model-to-model as well as model-to-code
transformation, we define a suite of meta-data for a
goal model, a task model, a context model, a
modality model and a functional core adaptor model.
Whereas separating the platform independent
aspects of an interactive system from those which
are platform dependent enables a design time
adaptation, the inclusion of context information
throughout the modelling process of both the
application business logic and the abstract user
interface enables a runtime adaptation.
To quantitatively compare the EMODE
methodology with existing standard approaches, we
are developing two demonstrators: the in-car travel
assistant and the mobile maintenance application. A
first version of the travel assistant which is
developed by standard tools is now fully functional;
work is in progress to produce it with the EMODE
tool chains, and to perform the comparison.
ACKNOWLEDGEMENTS
The EMODE project is partially funded by the
German Federal Ministry of Education and Research
(BMBF). We would like also to acknowledge the
contribution of René Neumerkel and Gerald Hübsch
to this paper.
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