TITLE:
An Interactive Expert System Based Decision Making Model for the Management of Transit System Alternate Fuel Vehicle Assets
AUTHORS:
Michael L. Vaughan, Ardeshir Faghri, Mingxin Li
KEYWORDS:
Expert System Framework, Alternative Fuel Bus, Decision Making Process, Information Management, Transit
JOURNAL NAME:
Intelligent Information Management,
Vol.9 No.1,
December
26,
2016
ABSTRACT: Traditionally, the process used by public
transportation entities to determine the acquisition strategy for new vehicle
asset is based upon a broad range of criteria. Vehicle cost has been cited as
one of the more critical factors which decision makers consider. It is
currently a common practice to consider other factors (life-cycle cost, fuel
efficiency, vehicle reliability, environmental effects, etc.) that contribute
to a more comprehensive approach. This study investigates the next generation
of advancements in decision making tools in the area of the application of
methods to quantify and manage uncertainty. In particular, the uncertainty
comes from the public policy arena where future policy and regulations are not
always based upon logical and predictable processes. The fleet decision making
process in most governmental agencies is a very complex and interdependent
activity. There are always competing forces and agendas within the view of the
decision maker. Rarely is the decision maker a single person although, within
the transit environment, there is often one person charged with the
responsibility of fleet management. The focus of this research examines the
decision making of the general transit agency community via the development of
an expert systems prototype tool. A computer-based prototype system is
developed which provide an expert knowledge-based recommendation, based upon
variable user inputs. The results shown in this study show that a decision
making tool for the management of transit system alternate fuel vehicle assets
can be modeled and tested. The direct users of this research are the transit
agency administrations. The results can be used by the management teams as a
reliable input to inform their urban transit buses expansion decision making
process.