Date of Award

Summer 2017

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Computer Science

Committee Director

Tamer Nadeem

Committee Member

Kurt Maly

Committee Member

Ravi Mukkamala

Committee Member

Mecit Cetin

Abstract

Inefficiency in transportation networks is having an expanding impact, at a variety of levels. Transportation authorities expect increases in delay hours and in fuel consumption and, consequently, the total cost of congestion. Nowadays, Intelligent Transportation Systems (ITS) have become a necessity in order to alleviate the expensive consequences of the rapid demand on transportation networks. Since the middle of last century, ITS have played a significant role in road safety and comfort enhancements. However, the majority of state of the art ITS are suffering from several drawbacks, among them high deployment costs and complexity of maintenance.

Over the last decade, wireless technologies have reached a wide range of daily users. Today's Mobile devices and vehicles are now heavily equipped with wireless communication technologies. Bluetooth is one of the most widely spread wireless technologies in current use. Bluetooth technology has been well studied and is broadly employed to address a variety of challenges due to its cost-effectiveness, data richness, and privacy perverseness, yet Bluetooth utilization in ITS is limited to certain applications. However, Bluetooth technology has a potential far beyond today's ITS applications.

In this dissertation, we introduce itsBlue, a novel Bluetooth-based framework that can be used to provide ITS researchers and engineers with desired information. In the itsBlue framework, we utilize Bluetooth technology advantages to collect road user data from unmodified Bluetooth devices, and we extract a variety of traffic statistics and information to satisfy ITS application requirements in an efficient and cost-effective way.

The itsBlue framework consists of data collection units and a central computing unit. The itsBlue data collection unit features a compact design that allows for stationary or mobile deployment in order to extend the data collection area. Central computing units aggregate obtained road user data and extract a number of Bluetooth spatial and temporal features. Road users’ Bluetooth features are utilized in a novel way to determine traffic-related information, such as road user context, appearance time, vehicle location and direction, etc. Extracted information is provided to ITS applications to generate the desired transportation services. Applying such a passive approach involves addressing several challenges, like discovering on-board devices, filtering out data received from vehicles out of the target location, or revealing vehicle status and direction.

Traffic information provided by the itsBlue framework opens a wide to the development of a wide range of ITS applications. Hence, on top of the itsBlue framework, we develop a pack of intersection management applications that includes pedestrians’ volume and waiting times, as well as vehicle queue lengths and waiting times. Also, we develop a vehicle trajectory reconstruction application.

The itsBlue framework and applications are thoroughly evaluated by experiments and simulations. In order to evaluate our work, we develop an enhanced version of the UCBT Network Simulator 2 (NS-2). According to evaluation outcomes, itsBlue framework and applications evaluations show promising results. For instance, the evaluation results show that the itsBlue framework has the ability to reveal road user context with accuracy exceeding 95% in 25s.

ORCID

0000-0003-0950-9412

Available for download on Friday, October 25, 2019

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