Information Technology Reference
In-Depth Information
Additionally, the ODSS component drives the DRT control and managing centre,
receiving travel requests and determining the most appropriate service plans (which
vehicle? which route? which schedule?).
The proposed extended and integrated BI solution can implement most of the per-
formance measures reported before (Section 2), and easily translate them into the
form of traditional tables, graphs and reports. This includes making use of simple
dashboards. Most of these elements can be easily customized by end users, according
to their specific needs and options.
Data visualization can be seen as the process of translating information into a vis-
ual form (usually graphs and maps), enabling users (scientists, engineers and manag-
ers) to perceive the features of the data available, and, from that point, to help them to
make more effective decisions at different levels: strategic, tactical or (even) opera-
tional. For example, deciding on the design of service operations strategies or, simply
deciding on the realization of a functional regulatory (e.g. corrective) measure to en-
sure the normal functioning of the system or to minimize the impact of an anomalous
event (incident) that has occurred.
In the next section, some illustrative results of a given iteration of the above proc-
ess is reported and discussed. It shows the software viability in theoretical terms (de-
mand is defined randomly).
5
Illustrative Examples
In the following paragraphs, examples show the importance of adequate visualization
patterns according to specific nature of data recorded and information needed.
The examples are related to the design phase of a particular DRT transportation
system, before its implementation. No real information exists yet on its functioning,
so it is considered as a purely strategic and tactical decision process. In this case, the
simulation model component must be used in order to emulate what could happen at
any tested real-world scenario, in order to allow the evaluation of different options
(essentially, system objectives and rules).
In order to detect peak periods and understand correlation to service delays may be
worth using simple line charts of average traffic volumes and delays estimated in the
system, as a function of day-time. This should be done by taking into account the
average figures for relevant zones or intersections that affects each transport service.
Such information (patterns) can be also incorporated into adequate predictive models
of time arrivals at stops (e.g. for public panel information). Also, panels or dashboards
are very interesting and useful to the analyst, allowing an overview of the system and
discovery interaction between its various elements (tables, charts, combo box, etc.).
In order to perceive and monitor service levels in different directions from a given
urban center (e.g. incoming PT services bringing people to work at the morning
peak), may be worth using a rose-like diagram (Figure 5). This can be done per ser-
vice or group of services in each direction (e.g., north, west, south and east bands).
