TITLE:
Fuzzy Logic Inference Applications in Road Traffic and Parking Space Management
AUTHORS:
Ahmed Tijjani Dahiru
KEYWORDS:
Fuzzy Logic Inference, Universe of Discourse, Membership Functions, Parking Space, Traffic, Simulations, Surface Views, Rule Views
JOURNAL NAME:
Journal of Software Engineering and Applications,
Vol.8 No.7,
July
30,
2015
ABSTRACT: In modern motoring, many factors are
considered to realize driving convenience and achieving safety at a reasonable
cost. A drive towards effective management of traffic and parking space
allocation in urban centres using intelligent software applications is
currently being developed and deployed as GPS enabled service to consumers in
automobiles or smartphone applications for convenience, safety and economic
benefits. Building a fuzzy logic inference for such applications may have
numerous approaches such as algorithms in Pascal or C-languages and of course
using an effective fuzzy logic toolbox. Referring to a case report based on
IrisNet project analysis, in this paper Matlab fuzzy logic toolbox is used in
developing an inference for managing traffic flow and parking allocation with
generalized feature that is open for modification. Being that modifications can
be done within any or all among the tool’s universe of discourse, increment in
the number of membership functions and changing input and output variables etc,
the work here is limited within changes at input and output variables and bases
of universe of discourse. The process implications is shown as plotted by the
toolbox in surface and rule views, implying that the inference is flexibly open
for modifications to suit area of application within reasonable time frame no
matter how complex. The travel time to the parking space being an output
variable in the current inference is recommended to be substituted with
distance to parking space as the former is believed to affect driving habits
among motorist, whom may require the inference to as well cover other important
locations such as nearest or cheapest gas station, hotels, hospitals etc.