Information Technology Reference
In-Depth Information
the long-run (in most cases, the steady-state) behaviour of the system and its related
set of performance measures, thus allowing to perform its evaluation, e.g. compara-
tively against a “competing” scenario for the best in the pool for sustainability.
Transportation systems are, in general, intrinsically complex in terms of designing,
planning and analysis. For this reason, perhaps the majority of transportation planners
and analysts (e.g., traffic and mobility management bodies and agents, consultants)
already use simulation tools. There is a significant number of commercial solutions
available, such as EMME2, AIMSUN, DYNASMART, VISUM, DRACULA, etc.
The main problem with such tools is that they are intended to be used by specialists
since their outputs are usually very technical and do not integrate some other relevant
data analyses (e.g., financial data). Therefore, further analyses are needed in order to
reach to very specific and succinct relevant information that can deploy the decision
making. In other words, these tools are devoid of such benefits (process wizards,
clicks and drag-and-drops, and relevant-only information) that characterizes BI tools.
Additionally, Intelligent Transportation Systems (ITS) integrate a broad range of
IS/IT elements for gathering on-site data and transfer it to the central database(s) of
the enterprises or organizations. ITS also integrate the required hardware and software
to analyse and manage the information extracted from data. This means that usually a
huge amount of (operational) data is available. However, only a small fraction of this
amount is adequately translated into asset information that can be used by managers.
On the other hand, BI tools, as is, are aimed at enabling analysis of historical data
only. Therefore, they are not capable of giving accurate anticipations of future trends
as new scenarios of functioning are concerned. And, this is the usual shortcoming that
decision makers are faced to when using Decision Support Systems (DSS) purely
based on BI tools. Therefore, it is important to incorporate reliable predictive systems
capable of evaluating beforehand the impact of alternative or small changes in strate-
gic or tactical plans. This can be done by integrating what-if analysis, by means of
simulation, whose goal is to inspect the behaviour of a complex system under a given
scenario.
In recent years, what-if analysis has been incorporated in BI tools. For example:
SAP and SAS dedicated modules, MicroStrategy, Pentaho, QlikView, Powersim Stu-
dio, etc. Also, Microsoft has been integrating this technology in spreadsheets and
OLAP tools. However, these analyses rely on the application of forecasting models
and data-mining techniques on static historical data, thus heavily limiting the capabil-
ity of performing the evaluation of most scenarios, namely all those that are some-
what different from the existing one.
In order to overcome this shortcoming, we then propose, in Section 3, an integrated
approach that fundamentally consists on setting up an iterative (and user interactive)
loop between a compatible simulation model or tool and a BI tool to support decisions
at the strategic and tactical levels.
The herein proposed approach is particularly welcome for the designing and plan-
ning of DRT systems. Its potential interest relies on identifying a set of questions that
can then be answered with effectiveness and more efficiently than before. In particu-
lar, such set comprises a list of strategic and tactical issues that are of crucial
Search WWH ::




Custom Search