Decision making model for the management of transit system alternate fuel infrastructures through the utilization of an interactive expert systems interface

Date
2017
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University of Delaware
Abstract
There are many factors in the decision making process which, when taken into account, lend themselves to a reasonable fleet management approach that is both robust and sustainable in a dynamic and technologically rich environment. The work in this area falls under the general area of Transportation Engineering with a more broad connection to Civil Engineering. ☐ 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 that contribute to a more comprehensive approach. Some of these other factors are as follows: 1. life-cycle cost, fuel efficiency 2. Vehicle reliability 3. Environmental effects ☐ Although federal agencies, e.g. Federal Transit Administration (FTA), have published several reports investigating and comparing alternative fuel buses, those reports do not directly suggest which technology is a dominant choice for a specific state. (Shahpar, 2010) ☐ The determination of the most appropriate alternative fuel bus asset for a given application is not necessarily that straight forward. The typical bus fleet is developed over a broad time horizon with each asset being acquired to meet a certain agency need or to close a perceived gap in the delivery of public transportation service. Therefore; as new assets are considered, it is critical for the fleet manager to consider as many factors of the fleet infrastructure to better ensure the positive impact that the newly acquired asset will have on fleet performance relative to the overall service goals and objectives of the fleet. ☐ This study investigates a broad range of alternative-fuel bus technologies and the associated factors that will inform the decision making process. Further, this work utilizes the inventory and understanding of the range of technology factors and leverages the perspective (knowledge) of industry experts on each of these factors to develop an expert systems decision making philosophy to aid in the adoption of industry standards, best practices, consistency and sustainability in fleet asset management over time. ☐ This study investigates what I believe is 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 that 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 based upon the Exsys Corvid® software platform. The platform has been selected for its broad capability in capturing expert decision making knowledge and data in an easy to understand user applicable format. ☐ A computer-based prototype system is developed, within the Exsys Corvid® environment, 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 user 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.
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