Undergraduate Research Program – Intelligent Urban Parking
The purpose of this document is to propose an IMSE Undergraduate Research Project that will
investigate the underlying technologies needed to support the development of an intelligent
parking system that will detect available parking in a congested and dynamic unban environment
and direct system subscribers to available parking based in their user profile. The parking
system at UTA will serve as a good example environment.
Problem – Urban parking systems typically have limited resources. In this environment the
number of desirable parking spaces is much smaller than the number of parking subscribers that
have parking privileges provided they can find a spot. In dynamic environments, when users
only need parking for a limited time period, and these times are frequently different for each
parking subscriber, reserved parking spaces are often inefficient and hold a valuable resource for
a user who will not utilize it 100% of the time. During peak utilization periods, parking
subscribers are forced to search for available parking without any information that might help
them predict the likelihood of finding a suitable spot.
Proposed Research – This undergraduate research project will develop the requirements for an
intelligent parking system designed to direct system subscribers to suitable parking locations
based on the real-time utilization of the parking resources in the system. Once a set of
requirements have been proposed, the undergraduate researcher will perform a functional
analysis of a potential Intelligent Parking System that can reduce the time users spend searching
for available parking and increase the utilization of the most desirable parking resources.
The undergraduate researchers will investigate the use of existing technologies like cell phone
applications, dynamic digital displays, information systems, and machine vision to support the
development of various system concepts. Software prototyping, scale models, and computerbased simulation can be used to access the feasibility of various system components. Various
solutions to the problem of intelligent parking can be proposed and analyzed.
Project Advisor:
Brian Huff
Associate Professor
Woolf Hall, Room 325 E
Email: bhuff@uta.edu