A Driver, Vehicle and Road Safety System Using Smartphones Metadata

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Title

  • Main Title A Driver, Vehicle and Road Safety System Using Smartphones

Creator

  • Author: Gozick, Brandon
    Creator Type: Personal

Contributor

  • Chair: Dantu, Ram
    Contributor Type: Personal
    Contributor Info: Major Professor
  • Committee Member: Akl, Robert G.
    Contributor Type: Personal
  • Committee Member: Sweany, Philip H.
    Contributor Type: Personal

Publisher

  • Name: University of North Texas
    Place of Publication: Denton, Texas
    Additional Info: www.unt.edu

Date

  • Creation: 2012-05

Language

  • English

Description

  • Content Description: As vehicle manufacturers continue to increase their emphasis on safety with advanced driver assistance systems (ADAS), I propose a ubiquitous device that is able to analyze and advise on safety conditions. Mobile smartphones are increasing in popularity among younger generations with an estimated 64% of 25-34 year olds already using one in their daily lives. with over 10 million car accidents reported in the United States each year, car manufacturers have shifted their focus of a passive approach (airbags) to more active by adding features associated with ADAS (lane departure warnings). However, vehicles manufactured with these sensors are not economically priced while older vehicles might only have passive safety features. Given its accessibility and portability, I target a mobile smartphone as a device to compliment ADAS that can bring a driver assist to any vehicle without regards for any on-vehicle communication system requirements. I use the 3-axis accelerometer of multiple Android based smartphone to record and analyze various safety factors which can influence a driver while operating a vehicle. These influences with respect to the driver, vehicle and road are lane change maneuvers, vehicular comfort and road conditions. Each factor could potentially be hazardous to the health of the driver, neighboring public, and automobile and is therefore analyzed thoroughly achieving 85.60% and 89.89% classification accuracy for identifying road anomalies and lane changes, respectively. Effective use of this data can educate a potentially dangerous driver on how to operate a vehicle safely and efficiently. with real time analysis and auditory alerts of these factors, I hope to increase a driver's overall awareness to maximize safety.

Subject

  • Keyword: Transportation
  • Keyword: safety sensors mobile phone

Collection

  • Name: UNT Theses and Dissertations
    Code: UNTETD

Institution

  • Name: UNT Libraries
    Code: UNT

Rights

  • Rights Access: public
  • Rights Holder: Gozick, Brandon
  • Rights License: copyright
  • Rights Statement: Copyright is held by the author, unless otherwise noted. All rights Reserved.

Resource Type

  • Thesis or Dissertation

Format

  • Text

Identifier

  • Archival Resource Key: ark:/67531/metadc115086

Degree

  • Academic Department: Department of Computer Science and Engineering
  • Degree Discipline: Computer Engineering
  • Degree Level: Master's
  • Degree Name: Master of Science
  • Degree Grantor: University of North Texas
  • Degree Publication Type: thesi

Note

  • Embargo Note: Restricted until June 1, 2017
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