Computer Science and Engineering, Department of

 

Date of this Version

7-2011

Comments

A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfilment of Requirements For the Degree of Master of Science, Major: Computer Science, Under the Supervision of Lisong Xu and Wenbo He. Lincoln, Nebraska: July, 2011

Copyright 2011 Hongwei Wang

Abstract

In metropolitan areas, parking management influences drivers search time and cost for parking spaces, parking revenue, and traffic congestion. The wide deployment of wireless parking meters with sensing and communications capabilities allows the parking authority to monitor the state of each parking space in real time and optimize the parking management.

In this thesis, we study state-of-the-art parking policies in smart parking systems, and show that the smart parking system needs to be "smarter". Our design goals of the smart parking systems include: (1) simplify the operations of parking systems, (2) improve drivers' satisfaction, (3) increase parking revenue, and (4) alleviate traffic congestion. Through analysis and simulations, we first show that the proposed reservation-based parking policy has the potential to achieve the above goals. We then model the behavior of both service providers and drivers in smart parking systems, and explore the dynamic pricing scheme to achieve the goals in smart parking system design.

Furthermore, we design and implement a prototype of Reservation-based Smart Parking System (RSPS) that allows drivers to effectively find and reserve the vacant parking spaces. With the real time tracking of parking status via various sensing technologies, a smart parking system will dynamically update the parking price according to the physical parking status, and the parking price will affect drivers decision on parking slot selection, therefore, affect the parking status. A smart parking system can be regarded as a full-fledged cyber-physical system (CPS). Through extensive experiment based on real traffic traces and a real-world parking map, the results show that the proposed reservation-based parking policy has the potential to simplify the operations of parking systems, as well as alleviate traffic congestion caused by searching for parking.

Adviser: Lisong Xu and Wenbo He

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