Interactive Localisation System for Urban Planning Issues - Efficient Decision Support Systems: Practice and Challenges from Current to Future - page 461

nets (neither underground for archaeology rests nor in elevation for landscape facets) and
the search of the best location for destination places (such as public services) becomes as
crucial as the improvement of the existing mobility net.
However, saturation of the built territory places further problems connected to the settled
urban texture, when searching new locations for different functions (i.e. impossibility to
change the land destination, cost of the area, compatibility among functions and existing
buildings); in this context, it is inadequate to analyze an ideal distribution of functions based
on a perfect mobility net.
For these reasons it is crucial to find sub-optimal solutions considering all the existing
bonds, taking into consideration the best benefits for citizens; and citizens themselves try to
attain the same goal. In fact, auto-organisation of all urban systems is nowadays a milestone
of urban theories (Bertuglia, 1991, Donato and Lucchi Basili, 1996). Auto-organisation in
some way can be associated to the old general notion of level of satisfaction on the same
indifference curve from the Bid-Rent Theory (Alonso, 1964).
3. General description
Considering the cultural background, the system ULISSE (Urban Location Interactive
System for SErvices) here described is based on a model developed to help the planners in
finding the sub-optimal location for public services, considering the access time (that the
users spend) as a function to be minimized (De Lotto and Ferrara, 2001).
The system is based on a static model associated with the analysis of location-like problems
in an urban context (Drezner, 1995). This kind of problem is usually stated as follows: given
m clients and n potential sites for locating prespecified facilities, taking into account the
profit deriving from supplying the demand and the cost for setting up the facility in
question, select an optimal set of facility locations (Dell'Amico et al. 1997).
In order to face the problem, a classical way is to define a global cost function associated
with a certain location decision to be minimized. The cost function (named C in this paper)
can rely, for instance, on the actual cost to build and run the facility together with the costs
paid by the facility clients. The first type of cost can be reasonably regarded as independent
of the site chosen for location and it is not so relevant in the minimization process. In
contrast, the costs paid by the facility clients determine a distribution of the potential users
on the territory, significantly influencing the traffic flows through the transportation
networks connecting the possible facility locations.
In a real urban context, the concept of “client” can be naturally replaced with the concept of
“vehicle” or “transportation means”, since it is impossible to ignore the presence of an
underlying transportation network through which the i-th client reaches the j-th facility
(Cascetta 1990, Gelmini 1986). According to this basic consideration, the model proposed in
this paper describes the road network as an electric network, enabling to evaluate the
incremental traffic due to the access to the service. It describes each lane of a road as an
oriented link, characterized by (time-varying) parameters, such as the travel time at given
unsaturated conditions. Road intersections are represented as nodes with inflows and
outflows. The propagation delays due to the presence of traffic lights (Cantarella and Festa,
1998) and non homogeneous flows are also taken into account. Finally the effect of the
location of a facility in a precise site over the surrounding extended area is modeled.
The evaluation of the “temporal” use of the urban services is nowadays a fertile
investigation field (Bonfiglioli, 1997).