![](bg6.png)
as to direct genetic operations in such areas. This al-
gorithm could be directly applied to feed the Traffic
Forecasting Center (Fig. 3c). The traffic flow deter-
mined in this way could be directly used by the Dy-
namic Routing Engine (Fig. 3d).
5 CONCLUSIONS
In this paper an architecture was described for the
constant monitoring of road conditions and the con-
sequent real-time update of routes affected by prob-
lematic traffic conditions.
The system relies on a Dijkstra-likealgorithm and,
since this approach is not suitable to handle dynamic
large-scale problems, a first bibliographic research
was carried out in order to compare differentsolutions
to the search of optimal routes in the real-time case.
Some authors indicate that good performances can be
achieved using virus-evolutionary genetic algorithms,
and a variant of the proposed architecture was conse-
quently sketched.
Future work will be devoted to the refinement of the
considered approach and to suitable simulations.
ACKNOWLEDGEMENTS
This work was supported by the PEGASUS project,
financed by the Italian Ministry of Economic Devel-
opment.
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AN INTEGRATED ARCHITECTURE FOR INFOMOBILITY SERVICES - Advantages of Genetic Algorithms in
Real-time Route Planning
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