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Evaluation of Vehicle Positioning Accuracy using GPS-Enabled Smartphones in Traffic Data Capturing

  • Author / Creator
    Yin,Na
  • Connected Vehicle (CV) technology aims to improve transportation management and system performance by incorporating advanced detection and communication system such as Global Positioning System (GPS), and smart devices to make roads and vehicles better equipped to exchange important information regarding road and travel conditions. GPS have emerged as the leading technology to provide location information to various location based services. With an increasing smartphone penetration rate, as well as expanding spatial and network coverage, the idea of combining GPS positioning functions with smartphone platforms to perform GPS-enabled smartphone-based traffic management and data monitoring is promising. This study presents a field experiment conducted along Whitemud Drive (a section of Connected Vehicle Test Bed in Edmonton, Alberta, Canada), Queen Elizabeth Highway, and various urban arterial roadways using a GPS-enabled smartphone, cellular positioning technique, professional GPS handset and combination of smartphone and Geofence. The relative positioning errors and the data collection performances using the aforementioned technologies were evaluated and compared. The characteristics and the relationships between the positioning errors and traffic related factors are investigated using regression analysis. The results indicate that GPS-enabled smartphones are capable of correctly positioning 92% of the roadway segments to Google Earth, while achieving accuracy of less than 10 meters for 95% of the data. Using a cellular positioning technique, cell-IDs were correctly identified in repeatable trials with accuracy levels much lower than the smartphone-GPS positioning. Using combination of smartphone positioning and Geofence are promising in finding accurate positions and timestamps. In all scenarios, the use of four data source for obtaining location and traffic condition is feasible; and particularly, using GPS-enabled smartphones and/or its combination with Geofences can provide good accuracy level for location and traffic state parameter estimates.

  • Subjects / Keywords
  • Graduation date
    2014-11
  • Type of Item
    Thesis
  • Degree
    Master of Science
  • DOI
    https://doi.org/10.7939/R34X54Q9Q
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
  • Language
    English
  • Institution
    University of Alberta
  • Degree level
    Master's
  • Department
    • Department of Civil and Environmental Engineering
  • Specialization
    • Transportation Engineering
  • Supervisor / co-supervisor and their department(s)
    • Qiu, Tony (Civil and Environmental Engineering)
  • Examining committee members and their departments
    • Kim, Amy (Civil and Environmental Engineering)
    • Arturo Sanchez-Azofeifa, G (Earth and Atmospheric Sciences)